Trust in the Public Sphere

### **Chapter 9**

## Significant Role of Trust and Distrust in Social Simulation

*Akira Ishii, Yasuko Kawahata and Nozomi Okano*

### **Abstract**

This paper introduces the Trust-Distrust Model and its applications, extending the Bounded Confidence Model, a theory of opinion dynamics, to include the relationship between trust and mistrust. In recent years, there has been an increase in the number of cases in which the prerequisites for conventional communication (e.g., the other person's gender, appearance, tone of voice, etc.) cannot be established without the exchange of personal information. However, in recent years, there has been an increase in the use of personal information, such as letters and pictograms "as cryptographic asset data" for two-way communication. However, there are advantages and disadvantages to using information assets in the form of personalized data, which are excerpts of personal information as described above. In the future, the discussion of trust value in the above data will accelerate in indicators such as personal credit scoring. In this paper, the Trust-Distrust Model will be discussed with respect to theories that also address charismatic people, the effects of advertising, and social divisions. Furthermore, simulations of the Trust-Distrust Model show that 55% agreement is sufficient to build social consensus. By addressing this theory, we hope to use it to discuss and predict social risk in future credit scoring discussions.

**Keywords:** opinion dynamics, trust, distrust, social simulation, consensus building, social division

### **1. Introduction**

In society, people have different opinions and are influenced by the opinions of others. It is opinion dynamics that simulate what kind of opinion distribution it will form. Ideally, people in a society should be bound together by trust. However, in reality, people often distrust each other and rebel against each other. In this chapter, we will apply opinion dynamics to take into account the distrust between such people and describe how trust and distrust affect the composition of society.

Opinion dynamics is a field that has been studied for a long time with applications to consensus building and elections in society [1, 2]. The transition of social discussions leading to consensus building is an old problem, but it is also an important theme in the analysis of various communications on the Internet in modern society. The opinion dynamics of binary opinions (agree and disagree or agree and ignore) have long been studied in analogy with magnetic physics [3–9]. In addition, since 2000, the Bounded Confidence Model, which analyzes opinions not as binary values but as continuously varying quantities, has been presented, and more precise studies have been conducted [10–14].

However, the conventional Bounded Confidence Model implicitly assumes social consensus. In Gérard Weisbuch et al. [10] and Hegselmann-Krause [11], which are representative theories of the Bounded Confidence Model, the opinions of individual people are expressed as Ii(t) in the following equation. Here, the coefficient Dij, which indicates the degree of influence by other people's opinions, is limited to positive values.

$$I\_i\left(\mathbf{t}\right) = \sum\_{\boldsymbol{\upbeta}} D\_{\boldsymbol{\upbeta}} I\_{\boldsymbol{\upbeta}} \tag{1}$$

In the Bounded Confidence Model, the coefficient is considered to be a factor that represents the speed of convergence of opinions. If the coefficient is limited to a positive value, the opinions of everyone converge without fail, and the larger the positive value, the faster the convergence. In other words, it is not the results of individual simulations that cause the convergence of social opinions, but rather the Bounded Confidence Model [10–14] itself, in which the convergence of social opinions is inherent from the beginning.

The reality of opinions in society is that not all opinions can be agreed upon. In social issues, it is rather rare to reach a consensus. In reality, we all experience cases where we feel opposition to someone's opinion. Therefore, Ishii and Kawahata extended the Bounded Confidence Model by introducing repulsion and distrust of opinions [15–20]. Simply put, the extension is that the coefficients are not limited to positive values, but negative values are introduced, and positive values indicate a trust relationship, while negative values indicate a distrust relationship. If the coefficient is negative, the opinions will be separated from each other every moment. In other words, they will never reach a consensus. This new theory of opinion dynamics is called the Trust-Distrust Model.

Using this theory of opinion dynamics, calculations have been made for the case of a person who is charismatically popular in society [20] and for the case of a person who is disliked by society as a whole [18], and calculations can also be made for the case of a society splitting, so this theory of opinion dynamics has the potential to enable social simulation calculations for many social movements.

In addition, the theory of opinion dynamics with multiple axes of opinion has been proposed by Ishii and Okano, and analysis has been conducted with two axes of opinion, so-called "official stance" and "real opinion" [21].

### **2. Trust and distrust in societies**

Even between individuals with limited time and space, active exchange of opinions has become possible [22]. In recent years, there are more and more cases in which the prerequisite information for conventional communication (e.g., the other person's gender, appearance, tone of voice) cannot be established without exchanging personal information. In recent years, however, immediate two-way communication with excerpts of personal information such as letters and pictograms has become the norm. However, there are advantages and disadvantages to using information assets in the form of personalized data, which are excerpts of personal information as described above. The above discussion has already started in the 1950s when the use of the Internet was limited in the U.S. and the former Soviet Union; in the early 1990s, the Internet became available to the general public and the discussion was accelerated based on the concept of the information highway. Today, the status of information asset management and personalized data management differs from country to country. This has led to various problems in terms of economic loss and

### *Significant Role of Trust and Distrust in Social Simulation DOI: http://dx.doi.org/10.5772/intechopen.101538*

education related to the development of human resources involved in the proper management of information assets using data (e.g., data scientist training, legal development, moral and ethical education in handling data). In Japan, on the other hand, with the spread of mobile communications, the flat-rate system for telecommunications was applied early and actively operated at a rapid pace from the late 1990s to the early 2000s. In particular, the flat-rate system was introduced at a lower cost than in neighboring Asian countries, and advanced efforts were made in terms of information transmission. However, against the backdrop of this rapid progress, it is difficult to say that awareness-raising and legislation regarding the use of the Internet among the compulsory education generation and the generation that is not familiar with Internet literacy and cyber security (assumed to be socially vulnerable groups such as children and the elderly) has progressed. It is possible that communication is repeatedly evolving. In recent years, there have been cases of fake news being disseminated on a large scale. As a result, there have been cases where misconceptions about personal information have spread. In some cases, this may even occur in the community, resulting in a "big wave of information" on an individual basis. While we cannot be certain that there are adequate warnings and laws regarding how to use the Internet, communication may continue to evolve. Therefore, social networking services are always at risk of becoming hotbeds of conflicts and criminal activities that sometimes spill over into society as a whole, and risk management for them has been actively discussed in recent years. In particular, the COVID-19 disaster has increased the need for risk management due to the increased use of online communication. This issue raises concerns not only about the parties involved, but also about the responsibility of those who accidentally spread fake news that pose a great risk to the lives of both parties. How to deal with such cases will need to be discussed in the future. On the other hand, there are concerns about the emergence of a new "digital divide". In the past, the divide over the superiority of handling computer technology itself was a hot topic in Japan from 2004 to 2005. However, the new "digital divide" assumes that computer technology is available to some extent regardless of gender or age. The differences are differences in literacy due to differences in the ability to transmit information (such as loudness of voice) and extract information. It can be assumed that there will be cases of false understanding, such as being evaluated by the number of people on the web. In this regard, since the beginning of this year, social networking sites have taken measures such as speech control and account restrictions to ensure fairness in elections (e.g. in the US and English-speaking countries). However, in order to ensure fairness, there is a limit to large-scale policing through mechanical processes in the Japanese sphere, which has a complex linguistic context including English, katakana, hiragana, and kanji. Therefore, it can be said that education also requires reading comprehension in all kinds of texts and a perspective on preserving the information resources of individuals. In this regard, those who are vulnerable in the information environment, such as the generation that has not been adequately educated on cyber security, may be at risk of various fragmentation. As a result of this information gap, a threshold of distrust and trust in communication occurs, and sometimes there are scattered cases of major mistakes such as major social fragmentation, deadly attacks, and slander against completely disinterested entities. In the case of socially vulnerable people, there is a limit to the legal measures that can be taken without financial benefits such as hiring a lawyer, and there is a risk that socially vulnerable people who should be protected will be left defenseless or denounced. To remedy them, social protection and remedy mechanisms in online communities, such as digital citizenship, are also urgently needed, and even within those communities, consensus building, trust building, and to some extent, thresholds occur. In addition, slander and defamation may be committed without the person being aware of it and he or she may be held responsible for it.

Only those who are in a superior position to apply the law are protected and enjoy many benefits, while those who are not in a position to denounce based on legal grounds may cry themselves to sleep or suffer losses without any social guarantee. In such cases, although there are problems such as surveillance society, digital citizenship, and other network communication in neighborly relations, the formation of communities that protect each other regardless of social class is more important. And there are expected to work as part of care work in online communities. In these elements, it can be said that mutual care communication based on mutual "trust" and very close relationships, neighborly relationships, is promoted. It can be hypothesized that these online pseudo-societies, which promote the building of invisible trust relationships formed between distant and nearby communities, have something in common with the wider society. Since the rapid spread of public networks, there have been growing expectations for elucidating the mechanisms of social phenomena that have become difficult to visualize and quantify [23]. However, in order to analyze the exchange of opinions left in the vast amount of log data in modern society, it goes without saying that a theory that corresponds to quantitative analysis, focusing on integration with analysis to large-scale data, is necessary. In addition, slander and defamation may be committed without the person being aware of it and he or she may be held responsible for it. Only those who are in a superior position to apply the law are protected and enjoy many benefits, while those who are in a position not to be denounced on legal grounds may cry themselves to sleep or suffer losses, without any social guarantee. Similar functions are ensured in functions such as suggestions in online search behavior and product recommendations in e-commerce, etc. In addition, opinions that infer our trust or distrust, which constitute the recommendation function, become "opinion aggregates" or "generalization models" that are automatically returned to us through public networks. These are the results of online consensus building; in COVID-19, generalized models and recommendations for various social crisis situations will be developed and analyzed based on large-scale data such as our behavior logs and opinions. However, the global spread of public networks has not been positive in all aspects, and while COVID-19 has increased excessively, problems such as online slander have also been highlighted. This chapter touches on those issues as well. In particular, a case can be envisioned where public opinion is formed from the aftermath of unconscious consensus building. This is the case today, when populism and propaganda are rampant. However, the use of online media was pioneered in the 2020 U.S. presidential election, and typical social networking sites such as Facebook and Twitter have been suppressed, and regulations and laws are being revised at a rapid pace. From this point of view, it can be inferred that the nature of online communication is entering a transitional period after COVID-19 and the 2020 U.S. presidential election. It is now possible to pseudo-analyze various opinions in society through online logs. Theories for analyzing the process of consensus building in society (or small groups) have long been proposed and studied from various perspectives [10–14]. However, in order to analyze the exchange of opinions left in the vast amount of log data of modern society, it goes without saying that a theory that corresponds to quantitative analysis, focusing on integration with analysis to large-scale data, is necessary. There are two main types of theories of opinion dynamics. One is the theory that treats contradictory conditions and discrete opinions as 1 (trust) and 0 (distrust), or 1 (trust) and -1 (distrust). In presidential elections in the U.S. and France, and in referendums such as those seen in Brexit, this dichotomous theory is more likely to be applied because voting takes place when there is one clear winner. The other method is the theory that regards opinions as a continuous value with one (or many) dimensions. For example, consensus building is often considered in this way [15–20]. As for the discussion of public health risk management in the COVID-19 disaster, which is imminent every

*Significant Role of Trust and Distrust in Social Simulation DOI: http://dx.doi.org/10.5772/intechopen.101538*

day as described above, the number of articles being updated and recorrected is increasing every day. Changes in information on the web provide a bird's eye view of the situation, which is often different from the expected case. In addition, there is an urgent need to "democratize security" in order to appeal to, resolve, and protect vulnerable members of society who do not fully understand cyber security. Depending on future legal decisions, significant changes may occur. In addition, there is a need to share security awareness in cyberspace as well as offline crime arrest rates in society. In addition, in various online communities, organizations may be formed to protect each other's security in the form of blockchain, just like the "Ren" (ex. creation critics' community) formed in the Edo period in Japan. In the aforementioned communities, there is a communication and consensus that can only be established if there is a clear relationship of trust and distrust. In recent years, while consensus-based communication has increased, disparities and security issues have also been detected, and more and more fatal flaws and security errors in online communities have been uncovered that were not previously apparent. The mechanism by which these problems are discovered can occur when there is a sense of distrust among a certain number of people in a community. In the context of information and communication known as "technological warfare" or "quiet information warfare," the threshold values of parameters related to the sense of trust and distrust among communities are important information for communication to take place, but they are difficult to determine, quantify, and visualize clearly. Therefore, it is necessary to reason based on mathematical models, develop arguments and predictions, and confront possible risks and potential social problems. These issues, as well as election prediction, are themes that involve implicit understandings, such as floating and fixed votes, and consensus among regions, so we try to consider them together with social discussions in consensus building [15–21].

### **3. Opinion dynamics including both trust and distrust**

In the opinion dynamics proposed by Ishii named Trust-Distrust Model, the time evolution of people's opinions in the society is expressed by the following Equation [16].

$$m\Delta I\_i(\mathbf{t}) = c\_i A(\mathbf{t}) \Delta \mathbf{t} + \sum\_{j=1}^{N} D\_{ij} f\left(I\_i, I\_j\right) \left(I\_j - I\_i\right) \Delta \mathbf{t} \tag{2}$$

The first term on the right-hand side is the influence of external media such as advertising, mass media reports, and government publicity, where A(t) is the influence from mass media from time to time, and the coefficient ci is the coefficient of how much influence each person receives from that mass media. The coefficient Dij can be negative [15, 16]. Here, the function f(Ii,Ij) is a cutoff function that is ignored when the opinions are farther apart than a certain degree. Hegselmann-Krause [11] uses a simple step function, but here we use the Sigmoid function in the sense of a smooth cutoff.

$$f\left(I\_i, I\_j\right) = \frac{1}{1 + \exp\left(a\left(\left|I\_i - I\_j\right| - b\right)\right)}\tag{3}$$

Here, the coefficients of trust and distrust, Dij and Dji, are considered to be independent. Usually, Dij is an asymmetric matrix with Dij ̸= Dji. Moreover, Dij

**Figure 1.**

*Example of trust-distrust model calculation using Eq. (2). Two people. On the left is the case where two people are in a trust relationship with DAB > 0 and DBA > 0. On the right is the case where DAB < 0 and DBA < 0, and the two people are in a distrustful relationship.*

and Dji can take positive and negative values with different signs. A positive value means that i trusts j, while a negative value means that i does not trust j. Also, m is the strength of will of agent "i". For large values of m, the agent "i" is not so much influenced by mass media or other people's opinions.

The Trust-Distrust Model can be used to calculate the case of a person who is charismatically popular in society [22] and the case of a person who is disliked by society as a whole [18], and it can also be used to calculate the case of a society splitting up [23–25], so the Trust-Distrust Model has the potential to provide social simulation calculations for many social movements.

Here is a simple calculation using Trust-Distrust Model. **Figure 1** shows the opinion dynamics for the case of two people, where the left side of **Figure 1** shows the case where the two people trust each other (DAB > 0, DBA > 0). The right panel of **Figure 1** shows the case where two people in the calculation are shown as "A" and "B". distrust each other (DAB < 0, DBA < 0). The case of mutual trust can be found in Hegselmann-Krause [11], but the case of distrust cannot be calculated without this theory.

In this Trust-Distrust Model, the influence of the mass media is expressed by the first term on the right side of Eq. (2) called ciA(t). Here, A(t) is the amount of mass media coverage of the focal topic. The quantity is simply the product of the number of seconds and the number of channels that handle the topic, and the coefficient ci on this means that we can handle the fact that each person is affected differently by this mass media.

Based on Eq. (2), the individual opinions of the people, Ii(t), are calculated over time. We assume that opinions can take values from -∞ to +∞; Hegselmann-Krause [11] has 0 to 1, but Trust-Distrust Model has no upper bound on extreme opinions (and no lower bound if negative). In this case, the initial opinions of people are distributed as uniform random numbers in the range of −20 to +20.

What is important in Trust-Distrust Model is the coefficient Dij represented in Eq. (2). In a complete network where all people are connected to all people, there are N2 coefficients Dij that express trust or distrust between individual people. Ishii and Kawahata have shown that if more than 55% of the N2 Dij are positive, that is, trustworthy, the system will form a consensus [17]. This result is also true for random networks [26].

### **4. Consensus building in societies**

When people in a society are bound together by trust, they reach a consensus. This is the implicit assumption and conclusion of the bounded confidence model.

### *Significant Role of Trust and Distrust in Social Simulation DOI: http://dx.doi.org/10.5772/intechopen.101538*

The time required to reach consensus and whether one or more opinions are reached can be analyzed from the calculations of the bounded confidence model.

However, if people in the society as a whole are not necessarily bound by trust, it becomes uncertain whether they will reach a consensus or not. If all the people in a society distrust each other, it is obvious that they will not reach a consensus. Then, there is an interesting question that can be confirmed by a mathematical model: what is the ratio of trust and distrust that will lead to consensus formation?

First, we use the Trust-Distrust Model to calculate whether the entire society, assuming 300 people, will form a consensus in a situation where people's connections are mixed with trust and mistrust. Assume that these 300 people are connected by a complete network. Suppose that the coefficient of trust Dij connecting people occurs in a specified proportion of cases where the coefficient is a positive value determined by a random number between 0 and 1 and a negative value determined by a random number between −1 and 0. Let T be the proportion of positive or negative values of the trust coefficient Dij. If T = 1, the every trust coefficient Dij is positive. For example, if T = 0.5, then the positive and negative values are 50–50.

The results of the calculations are shown in **Figure 2** and **Figure 3** [19]. **Figure 2** plots the highest value of the opinion distribution for calculations from T = 0.45 to T = 1. Since the calculations are for 300 people, the vertical axis of **Figure 2** is 300 if consensus is achieved. The highest value of the distribution is over 200, indicating that the situation is close to consensus formation. On the other hand, at T = 0.45, the highest value of the opinion distribution is less than 20, suggesting that the opinion distribution does not have a sharp peak. Therefore, at T = 0.45, the situation is far from consensus building.

The above results were calculated for a complete network of 300 people. Since a complete network cannot be realized in society, calculations for the case where people are connected in a different network structure are also presented. The calculations were done for random networks and scale-free networks.

### **Figure 2.**

*Variation of the highest value of the opinion distribution with the proportion T of positive and negative values of the coefficient of confidence Dij.*

### **Figure 3.**

*The changes in the opinion distribution due to the ratio of positive and negative values of the coefficient of confidence Dij, T, are calculated for T = 0.5, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, and 0.60. N = 1000 in this calculation. The probability of people connecting in a random network is set to 30%.*

This can be seen in **Figure 3**, which shows the computation of the opinion distributions for T = 0.5, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, and 0.60. Let us assume that the entire society has 1000 people and is connected by a random network. The probability of people being connected is set to be 30%. As can be seen here, when T = 0.55 or higher, the opinion distribution has a sharp peak, indicating that a consensus has been formed. However, at T = 0.54, there is a peak, but it is not sharp, and at T = 0.53 or lower, the distribution of opinions is flattening out, clearly indicating that consensus has not been formed. The calculation for 300 people in the complete network is very similar to this calculation.

It is noteworthy that the highest value of the opinion distribution in **Figure 2** changes rapidly with the change of T. The peak of the opinion distribution appears after T = 0.5, and the height of the peak becomes higher after T = 0.55. In other words, the value of T determines whether a society is consensus-building or not. We can see that the borderline between the two is approximately T = 0.55.

The abrupt change in the highest value of the opinion distribution seen in **Figure 2** suggests that there is a borderline at around T = 0.55 where society may or may not reach a consensus. In other words, if more than 55% of the relationships in the entire social network are trust relationships, consensus building is achieved in the entire society. This means that it is not necessary for all relationships to be trusting in order for the entire society to reach consensus, but if more than 55% of the relationships are trusting, the society will reach consensus.

This conclusion suggests that in a democracy, for example, if more than 55% of the people support a certain policy in an election, it is possible for society to reach a consensus. It also suggests that it is difficult to reach a consensus when there is a strong opposition between those in favor and those against, such as when the number of those in favor is less than 55%. Thus, this conclusion is interesting as an application to political science.

The conclusion that 55% is the borderline of social consensus is very striking. However, I wonder if this conclusion is the same no matter what network structure people are connected to. **Figure 4** below shows a calculation for a random network of 1000 people, where the probability of joining the random network is assumed to be 1%.

**Figure 4** shows that the sharp peak of the opinion distribution disappears completely at T = 0.6, and the sharp peak representing consensus emerges at about T = 0.75. In other words, if people's connections are sparse, such as the probability of joining in a random network is 1%, 55% is not the boundary of consensus formation.

For this quantitative check, we calculate the following quantity. This is the sum of the differences in the opinions of N people.

*Significant Role of Trust and Distrust in Social Simulation DOI: http://dx.doi.org/10.5772/intechopen.101538*

$$\mathcal{W} = \frac{\sum\_{i} \sum\_{j} \left| I\_i(t) - I\_j(t) \right|}{\sum\_{i} \sum\_{j} \left| I\_i(0) - I\_j(0) \right|} \tag{4}$$

This W is W = 1 if the width of the opinion distribution remains the same over time, W < 1 if consensus is reached, and W > 1 if the opinion distribution is divergent without consensus.

Let us examine quantitatively the finding from previous researches [26, 27] that consensus is formed when positive trust between people in a society is at least 55% of all relationships. In **Figure 5**, we show the T dependence of W for various values of trustΔ. Dij is between -Δ to Δ. The calculation of **Figure 5** is N = 1600, the connection rate of the random network is 30%. Since there are fluctuations due

### **Figure 4.**

*The changes in the opinion distribution due to the ratio of positive and negative values of the coefficient of confidence Dij, T, are calculated for T = 0.8, 0.75, 0.72, 0.70, 0.65, and 0.60. N = 1000 in this calculation. The probability of people connecting in a random network is set to 1%.*

### **Figure 5.**

*The calculated W as a function of T, the proportion of positive values of the trust coefficient Dij. N = 1600.*  Δ *= 1.0. The average value of 10 calculations is used. The proportion 0.01, 0.05, 0.1, 0.5 and 1 is shown.*

to random numbers, the calculated values are averaged over five times. The green horizontal line represents W = 1. In other words, if the calculation is below this green line, the society forms a consensus.

**Figure 5** shows that the condition for consensus is satisfied at about T = 0.53– 0.55, regardless of the size of Dij. In particular, when Δ = 1.0, we can see that when T is close to 0.55, there is a sharp inclination toward consensus. Therefore, the 55% consensus threshold from previous studies is supported. However, the threshold for consensus depends very much on the connection rate of the network: in the calculation for N = 1600, if Δ is 1.0, then W = 1 is T = 0.545 when the connection probability of the random network is 30%, but T = 0.69 when the connection probability is 1%. This means that if the network is sparsely connected, the threshold value of T will rapidly increase. In other words, if the network is sparsely connected, it will be difficult for society to reach a consensus.

In our previous work [27], we have performed the same type of calculations on scale-free networks, which are said to be closer to real human connections in society than random networks. However, in the case of scale-free networks, a clear consensus threshold such as 55% does not emerge.

### **5. Charismatic person**

People in society are not uniform, but each individual is unique. A person who is especially popular among many people is called a charismatic person. In this section, we will use the Trust-Distrust Model to simulate the case of a charismatic person who is trusted by many people.

Here, a charismatic person is one who is popular with many people in society. Although being popular among others is not synonymous with being trusted by others, in this Trust-Distrust Model, a charismatic person is considered to be a positive value with a high coefficient of trust Dij from others to the charismatic person. Thus, a charismatic person is defined as follows. The coefficient of trust, Dij, is the strength with which person "i" is influenced by a person "j". Therefore, if the charismatic person is represented by "c" and Dic is the trust from person "i" to

### **Figure 6.**

*Simulation of a single charismatic person. The charismatic person is trusted by the people in the society with a trust coefficient Dic = 10, and the trust coefficients between other people in the society are determined by random numbers in the range of +1 to* −*1. The arrows show the opinion distribution of the charismatic person. The blue line in the opinion trajectory represents the opinion of a charismatic person, while the green line is a sample of the opinion trajectory of an ordinary person.*

*Significant Role of Trust and Distrust in Social Simulation DOI: http://dx.doi.org/10.5772/intechopen.101538*

**Figure 7.**

*Simulation of two charismatic persons. The charismatic persons are trusted by the people in the society with a trust coefficient Dic = 10. The blue line and red line in the opinion trajectory represent the opinions of a charismatic person, while the green line is a sample of the opinion trajectory of an ordinary person.*

the charismatic person. Dic is larger than the influence from other people, then the charismatic person will have more influence.

**Figure 6** shows the case where there is one charismatic person in a society of 300 people. It can be seen that many people have their opinions close to those of charismatic person. Thus, a charismatic person will be able to attract people with similar opinions. The more positive and larger the value of Dic, the stronger the effect. This is called being popular in society.

**Figure 7** shows the case where there are two charismatic people in the society. These two people are popular and have many people who agree with their opinions. If the two charismatic people are far apart in their opinions, a middle opinion group will be formed between their opinions, but if their opinions are close, there will be no middle ground and the society will be divided between them.

### **6. Mass media effect**

Another feature that distinguishes the Trust-Distrust Model from the traditional bounded confidence model is that it can calculate the effect of advertising on the formation of social opinion. In this section, we will consider the impact of advertising on people's opinions of society. In general, advertising is the use of mass media to convey people's messages [28]. Here, we do not touch on the specific method of advertising or the content of advertising but set the impact of advertising per unit time on people as A(t). A(t) can be thought of as the amount of advertising per day, e.g., the amount of money spent on advertising.

The first term on the right-hand side of Eq. (2) is A(t), where A(t) represents the strength of advertising added to society from time to time. This term of the impact of advertising is adopted with reference to the term introduced in the mathematical model of hit phenomena [29, 30], which analyzes the impact of advertising on society.

In this section, the opinions people have are expressed as one-dimensional numerical values. Therefore, an opinion with a positive value simply means that it is expressed as a positive numerical value, not that it is an affirmative opinion. The situation is the same for opinions with a negative value. Therefore, whether an opinion is positive or negative only implies the direction of the opinion on a particular topic. Whether an opinion is positive or negative does not mean that it

### *The Psychology of Trust*

supports or does not support a particular topic. For example, on the topic of cola, it is possible to assign a positive value to an opinion that likes Coca-Cola and a negative value to an opinion that likes Pepsi-Cola. Conversely, it is also possible to make the opinion that you like Pepsi-Cola a positive opinion and the opinion that you like Coca-Cola a negative opinion.

**Figure 8** shows the effect of advertising on the distribution of opinions. From left to right, the strength of advertising is A(t) = 0, 0.5, and 5.0. When A(t) = 5.0 on the right, social opinion distribution moves significantly in the positive direction. In other words, using Eq. (2), we can include the influence of advertising in our calculations.

If we define the advertising term A(t) as follows, we can concentrate the opinions of the people in the society into an arbitrary opinion.

$$A(t) = -A \tanh\left(aI\_i(t) - b\right) \tag{5}$$

Here, a represents how narrowly the opinion distribution should be concentrated, and b specifies where the opinion distribution should be concentrated. By setting these a and b, we can decide which and how much of society's opinions should be concentrated. An example of this is shown in **Figure 9**. However, what kind of advertising can have this kind of effect is still another question.

An example of this extreme simulation is shown in **Figure 10**. Here, the opinion of the whole society is negative at first, but due to the influence of strong advertising, the opinion of all people in the society changes to a positive value. We do not know what kind of advertising can actually have this kind of effect on society, but we have shown that it is possible in principle as a mathematical model.

In the first term on the right-hand side of Eq. (2) of the Trust-Distrust Model, which represents the influence of advertising, the influence of advertising can be added separately to each person in society by setting the coefficient ci. This shows that it is possible to calculate micro-targeting, which is known in the field of marketing.

Eq. (2) also shows that people are influenced both by advertising from the mass media and by the people they are connected to in society. Today, with the development of social media, some people are not exposed to information from mass media such as television. Therefore, we will use the Trust-Distrust Model to investigate whether people who are not exposed to information from the mass media are indirectly influenced by the mass media through the influence of people who are connected to them in society [31].

In **Figure 11**, we set the number of people in society as a whole at 1000, of which 100 people, or 10%, are not affected by mass media. The connections between people are random networks, and the calculations for the percentage of connections are

### **Figure 8.**

*It shows the effect of advertising on the distribution of opinions. From left to right, a(t) = 0, 0.5, 5.0. When a(t) = 5.0 on the right, social opinion moves significantly in the positive direction.*

*Significant Role of Trust and Distrust in Social Simulation DOI: http://dx.doi.org/10.5772/intechopen.101538*

**Figure 9.**

*Calculation of the concentration of the distribution of opinions in society under the influence of advertising, using Eq. (5). A = 5, a = 0.2. The values of b are (a) b = 0, (b) b = 10. (c) b =* −*10.*

### **Figure 10.**

*Calculation of the concentration of the distribution of opinions in society under the influence of advertising, using Eq. (5). Parameters are a = 5, a = 0.2. Value of b is b = 20.*

### **Figure 11.**

*Simulation of the movement of people who are not reached by the influence of mass media. Suppose the number of people in the society is 1000, and 100 people are not reached by the influence of mass media. Calculations are shown for random networks with connection probabilities of 30%, 10%, 5%, and 0.5%. The trajectory of the opinions of those who are influenced by the mass media is pink, and the trajectory of the opinions of those who are not reached by the mass media is blue. The coefficient of people's trust is set at a uniform random number in the range of 1 to* −*1, and the proportion of positive values is T = 0.6. The proportion of positive values is T = 0.6. The strength of advertising is a = 5.*

### **Figure 12.**

*Polarization of the distribution of opinions in society. (a) Polarization of opinions obtained by the bounded confidence model. The coefficient of trust Dij > 0 for everyone in the pink locus of opinion. (b) Polarization of opinion obtained with the trust-distrust model. The red and blue groups in the locus of opinion are consensus with Dij > 0 within the group and distrust with Dij < 0 between the groups.*

shown as 30%, 10%, 5%, and 0.5%. In **Figure 12**, the trajectory of the opinions of those who are influenced by the mass media is depicted in pink, and the trajectory of the opinions of those who are not influenced by the mass media is depicted in blue.

The calculation results show that when people's connections are sparse, some of the people who have not received the influence of mass media do not receive the influence of mass media even though they are connected to people in the society, and their opinions are about −40 and the trajectory of their opinions is horizontal. Even in that case, many people's opinions are moving in the direction influenced by the

### *Significant Role of Trust and Distrust in Social Simulation DOI: http://dx.doi.org/10.5772/intechopen.101538*

mass media, that is, in the positive direction, because of the connections between people in society, even if the influence of the mass media does not reach them.

On the other hand, when people are closely connected in random networks, as seen in the case of 30%, even those who are not reached by mass media influence reach consensus with those who are, indicating that opinions are moving in a positive direction influenced by mass media.

### **7. Division of society**

The Trust-Distrust Model takes into account not only trust and consensus among people in a society but also distrust and opposition among people. Thus, phenomena such as social division can be reproduced in the simulation. Social divisions are often caused by serious conflicts in society, which is different from the phenomenon calculated by the Bounded Confidence Model, in which there are multiple consensus opinions because the opinions are far apart. In this sense, the Trust-Distrust Model seems to be a more suitable opinion dynamics theory for dealing with social fragmentation and division.

The most typical example of social division would be the American Civil War. The American society at that time was divided into two positions, and the war took the form of a war between two uncompromising and polarized groups. Another example would be the Reformation in Europe in the 16th century. Modern American society also seems to be divided into conservative and liberal, as seen in the 2020 presidential election. In Japan, during the Meiji Restoration in the mid-19th century, Japanese society was divided into conservative and reformist factions, and there was a civil war that lasted over a year. In addition to the past examples of wars, many countries are divided over whether to prioritize medical countermeasures or minimize economic damage in response to the spread of COVID-19 today, for example. Such divisions of opinion in society cannot be handled by the Bounded Confidence Model, since they clearly disagree with each other and with the opinions of others.

In the bounded confidence model, people in the society are basically in a trust relationship. In the bounded confidence model, people in the society are basically in a trusting relationship, and the cause of the polarization of opinions is therefore not affected by distant opinions. In the bounded confidence model, people are not influenced by opinions that are too far apart from their own, so the distribution of opinions in society becomes multipolar and coalesces into multiple opinions [10, 11].

However, in the case of the Trust-Distrust Model, it can be assumed that people in a society are divided into, say, two groups, and the groups are in conflict with each other and distrust each other. **Figure 12** shows the polarization of opinions in the bounded confidence model and in the trust-distrust model. **Figure 13** shows the polarization of opinions in the bounded confidence model and the trust-distrust model. Although they look the same, in the bounded confidence model, all people in society are bound by trust, while in the trust-distrust model, people in society are divided by distrust.

More generally, we think of a society as being divided into multiple endogroups. A distinction is made between the relations between people within an endogroup and the relations between an endogroup and people in another endogroup. Tajfel's idea [32] is to describe the relationship between an in-group and another in-group as an out-group.

This polarization of social opinion based on the Trust-Distrust Model is expressed in the concept of In-group and Out-group proposed by Tajfel [32], and **Figure 13** shows a schematic diagram of the opinions of people in society according to Tajfel's concept. In **Figure 14**, TA and TB are the proportions of positive values of the coefficient of trust Dij within groups A and B, and TAB is the proportion of

### **Figure 13.**

*In-group and out-group based on Tajfel's proposal. TA and TB are the proportions of positive values of the coefficient of trust Dij within groups a and B, and TAB is the proportion of positive values of the coefficient of trust Dij between groups.*

### **Figure 14.**

*Two typical examples of the distribution of opinions in a divided society. (a), TA = TB = 0.8. TAB = 0. Group A and Group B form a consensus as In-group. However, with TAB = 0. (b), TA = TB = 0.5. TAB = 0.*

### **Figure 15.**

*Calculations using the trust-distrust model when society is divided into Group A and Group B. TA = TB = 0.55. TAB = 0.3, 0.5, 0.6, 0.8. The opinion trajectories of people in Group A are in red and those of people in Group B are in blue.*

positive values of the coefficient of trust Dij between groups. If TAB = 0, then the two groups are completely split as in **Figure 13** (b).

**Figure 14** shows two typical examples of the distribution of opinions in a divided society. In (a), TA = TB = 0.8. TAB = 0. Group A and Group B form a consensus as In-group. However, with TAB = 0, the trust between the groups is zero. On the other hand, in (b), TA = TB = 0.5. TAB = 0, Group A and Group B do not form a consensus because of insufficient trust in the group, but the trajectories of the two groups are repulsive and do not mix because of distrust in the Out-group.

A typical example of (a) in **Figure 14** would be the American Civil War, where society was completely divided, and war broke out. However, as far as the votes for the 2020 presidential election in the United States are concerned, the two candidates are competing in each state, and there is no regional division.

**Figure 15** shows the results when TA and TB are fixed at 0.55 and TAB is varied. Here, TAB is not zero, so even with TAB = 0.3, Group A, and Group B mix a little. When TAB = 0.8, the two groups are in an out-group trust relationship, and they form a single consensus. For these detailed calculations, please refer to References [33, 34].

### **8. Discussion and conclusion**

In this paper, we introduced a new theory of opinion dynamics, the Trust-Distrust Model. Trust and mistrust play a very important role in this opinion dynamics theory. Trust brings people to a consensus, while distrust makes people repel. The Trust-Distrust Model is a theory that is suitable for simulating this situation.

The Bounded Confidence Model is a theory of opinion dynamics in which opinions take continuous values, and the Trust-Distrust Model is an extension of the Bounded Confidence Model. The Trust-Distrust Model is an extension of the Bounded Confidence Model in two respects: the coefficient Dij is seen as the coefficient of trust between people, and when this value is negative, the relationship is distrustful. Also, the influence of mass media was incorporated as an external field to the differential equation that determines opinion. The extension of distrust as negative trust facilitates the simulation of social phenomena such as social divisions. It is possible to simulate consensus building as an In-group for each group in the society, and trust and distrust as Out-group among groups in detail. In this sense, the Trust-Distrust Model is a theory that facilitates the simulation of a real, complex society. The main theme of this paper is the consensus of information: "trust-distrust", the discussion of social impact through communication by various media formed by implicit understanding is represented by resistance to authority, populism, and risk. The focus tends to be on issues. Depending on the content and nature of the news, positive dissenting or agreeing opinions may have both similar and different tendencies depending on the source and content, and the ability of stakeholders to communicate in the discussion. The simulation results suggest that the network structure is significantly changed by the above. On SNS, we have already gradually introduced a mechanism to anticipate risks, such as (1) a mechanism to prohibit hackers from accessing the system with a system that is increasing in number mechanically, and (2) a mechanism to prohibit accounts due to posted content. Has been done. However, unpredictable behavior can occur. In addition, by accumulating information collectively, patterns for manipulating information will continue to grow. As mentioned above, in the 2020 US presidential election, strict regulations were imposed on large-scale web-based speech control and erroneous information transmission channels including bots. From this research, the network structure changes drastically due to the spread of erroneous information, the participation of untrustworthy information, the balance of the spread of reliable information, and

the construction of the related party network, and the opinion is that phase transition occurs at a certain threshold. It was suggested. Significant changes may occur in the future due to future legislative decisions. Furthermore, we think that it is necessary to have a shared awareness not only of the crime clearance rate offline but also of security awareness in cyberspace as a social convention. In that respect as well, it is important to check facts in an online-offline environment and form a communication community in consideration of the reliability of information for a diverse risk society, or if it is distrustful for a risk society, it is wrong. It is necessary to consider various cases such as discussions when problems are overloaded, and it can be said that it is necessary to learn from past cases and prepare for them from hypothetical simulation results and case studies. In the future, there will be an increase in twoway communication across time and space by anonymizing personal information such as letters and pictograms, and extracting them "as cryptographic asset data" to represent social events. However, there are advantages and disadvantages to using information assets in the form of personalized data, which are excerpts of personal information as described above. In the future, the discussion of trust value in the above data will accelerate in indicators such as personal credit scoring. In this paper, the Trust-Distrust Model will be discussed with respect to theories that also address charismatic people, the effects of advertising, and social divisions. Furthermore, simulations of the Trust-Distrust Model show that 55% agreement is sufficient to build social consensus. By working on this theory, we hope to use it to discuss and predict social risk in future discussions in credit scoring.

### **Acknowledgements**

This work is supported by JSPS KAKENHI Grant Number JP19K04881.

### **Author details**

Akira Ishii1 \*, Yasuko Kawahata2 and Nozomi Okano1


\*Address all correspondence to: ishii.akira.t@gmail.com

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Significant Role of Trust and Distrust in Social Simulation DOI: http://dx.doi.org/10.5772/intechopen.101538*

### **References**

[1] Castellano C, Fortunato S, Loreto V. Statistical physics of social dynamics. Reviews of Modern Physics. 2009;**81**:591-646

[2] Sîrbu A, Loreto V, Servedio VDP, Tria F. Opinion dynamics: Models, extensions and external effects. In: Loreto V et al., editors. Participatory Sensing, Opinions and Collective Awareness. Under- standing Complex Systems. Cham: Springer; 2017. p. 42

[3] Galam S. Rational Group Decision Making. A random field Ising model at T=0. Physica A. 1997;**238**(66)

[4] Sznajd-Weron, Sznajd J. Opinion evolution in closed community. International Journal of Modern Physics. 2000;**C 11**:1157

[5] Sznajd-Weron K, Tabiszewski M, Timpanaro AM. Phase transition in the Sznajd model with independence. Europhysics Letters. 2011;**96**:48002

[6] Galam S. Application of statistical physics to politics. Physica A: Statistical Mechanics and its Applications. 1999; **274**:132-139

[7] Galam S. Real space renormalization group and totalitarian paradox of majority rule voting. Physica A: Statistical Mechanics and its Applications. 2000;**285**(15):66-76

[8] Galam S. In: Morel L, Qvortrup M, editors. Are referendums a mechanism to turn our prejudices into rational choices? An unfortunate answer from sociophysics, Chapter 19 of The Routledge Handbook to Referendums and Direct Democracy. London: Taylor & Francis; 2017

[9] Galam S. The Trump phenomenon: An explanation from sociophysics. International Journal of Modern Physics. 2017;**B31**:1742015

[10] Weisbuch G, Deffuant G. Frédéric Amblard and Jean-Pierre Nadal: Meet, Discuss and Segregate! Complexity. 2002;**7**(3):55-63

[11] Hegselmann R, Krause U. Opinion dynamics and bounded confidence models, analysis, and simulation. Journal of Artificial Society and Social Simulation. 2002;**5**:1-33

[12] Jager W, Amblard F. Uniformity, bipolarization and pluriformity captured as generic stylized behavior with an agent-based simulation model of attitude change. Computational and Mathematical Organization Theory. 2004;**10**:295-303

[13] Wander Jager and Frédéric Amblard: Multiple attitude dynamics in large populations, In: the Agent 2005 Conference on Generative Social Processes, Models and Mechanisms. The University of Chicago. October 13-15; 2005

[14] Kurmyshev E, Juárez HA, González-Silva RA. Dynamics of bounded confidence opinion in heterogeneous social networks: Concord against partila antagonism. Physica. 2011;**A390**:2945-2955

[15] Ishii A, Kawahata Y. Opinion dynamics theory for analysis of consensus formation and division of opinion on the internet. In: Proceedings of The 22nd Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES2018). Sapporo, Japan: IES2018; 2018. pp. 71-76 arXiv:1812.11845 [physics.soc-ph]

[16] Ishii A. Opinion dynamics theory considering trust and suspicion in human relations. In: Morais D, Carreras A, de Almeida A, Vetschera R, editors. Group Decision and Negotiation: Behavior, Models, and Support. GDN 2019. Lecture Notes in Business

Information Processing Cham 351: Springer; 2019. pp. 193-204

[17] Ishii A, Kawahata Y. Opinion dynamics theory considering interpersonal relationship of trust and distrust and media effects. In: The 33rd Annual Conference of the Japanese Society for Artificial Intelligence **33** JSAI2019 2F3-OS-5a-05. Tokyo, Japan: JSAI; 2019

[18] Okano N, Ishii A. Isolated, untrusted people in society and charismatic person using opinion dynamics. In: Proceedings of ABCSS2019 in Web Intelligence 2019. New York: The Association for Computing Machinery; 2019. pp. 1-6

[19] Ishii A, Kawahata Y. New Opinion dynamics theory considering interpersonal relationship of both trust and distrust. In: Proceedings of ABCSS2019 in Web Intelligence 2019. New York: The Association for Computing Machinery; 2019. pp. 43-50

[20] Okano N, Ishii A. Sociophysics approach of simulation of charismatic person and distrusted people in society using opinion dynamics. In: Proceedings of the 23rd Asia-Pacific Symposium on Intelligent and Evolutionary Systems. Springer Nature Switzerland: Springer; 2019. pp. 238-252

[21] Ishii A, Okano N. Two dimensional opinion dynamics of real opinion and official stance. In: Proceedings of NetSci-X 2020: Sixth International Winter School and Conference on Network Science, Springer Proceedings in Complexity. Cham, Switzerland Springer; 2020. pp. 139-153

[22] Agarwal A, Xie B, Vovsha I, Rambow O, Passonneau RJ. Sentiment analysis of twitter data. In: Proceedings of the workshop on language in social media (LSM 2011). Portland, Oregon: Association for Computational Linguistics; 2011. pp. 30-38

[23] Watts DJ, Strogatz SH. Collective dynamics of 'small-world'networks. Nature. 1998;**393**(6684):440-442

[24] Okano N, Ishii A. Sociophysics approach of simulation of charismatic person and distrusted people in society using opinion dynamics. In: Proceedings of the 23rd Asia-Pacific Symposium on Intelligent and Evolutionary Systems. Springer Nature Switzerland: Springer; 2019. pp. 238-252

[25] Ishii A, Okano N. Social simulation of a divided society using opinion dynamics. In: Proceedings of the 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology. Melbourne, Australia: Academic Matters; pp. 660-667

[26] Ishii A, Kawahata Y. Theory of opinion distribution in human relations where trust and distrust mixed. In: Czarnowski I et al., editors. Intelligent Decision Technologies, Smart Innovation, Systems and Technologies. Vol. 193. Cham, Switzerland: Springer; 2020. pp. 471-478

[27] Ishii A, Yomura I, Okano N. Opinion dynamics including both trust and distrust in human relation for various network structure. 2020 International Conference on Technologies and Applications of Artificial Intelligence (TAAI). Taipei, Taiwan: IEEE; 2020:131- 135. DOI: 10.1109/ TAAI51410.2020.00032

[28] Okano N, Okada I, Ishii A. Spatial opinion dynamics incorporating both positive and negative influence in small-world networks, to be appeared in entropy

[29] Ishii A, Arakaki H, Matsuda N, Umemura S, Urushidani T, Yamagata N, et al. The 'hit' phenomenon: A mathematical model of human dynamics interactions as s stochastic process. New Journal of Physics. 2012;**14**:063018 (22 pp)

*Significant Role of Trust and Distrust in Social Simulation DOI: http://dx.doi.org/10.5772/intechopen.101538*

[30] Ishii A, Kawahata Y. Sociophysics analysis of the dynamics of peoples' interests in society. Frontiers in Physics. 2018. DOI: 10.3389/fphy.2018.00089

[31] Ishii A, Okano N. Sociophysics approach of simulation of mass media effects in society using new opinion dynamics. In: Intelligent Systems and Applications (Proceedings of the 2020 Intelligent Systems Conference (IntelliSys)). Vol. 3. Springer Nature Switzerland: Springer; 2021. pp. 13-28

[32] Tajfel H, Turner J. An integrative theory of inter-group conflict. In: Austin W, Worchel S, editors. The Social Psychology of Inter-Group Relations. Monterey, CA: Brooks/Cole; 1979. pp. 33-47

[33] Ishii A, Okano N, Nishikawa M. Social simulation of intergroup conflicts using a new model of opinion dynamics. Frontiers of Physics. 2021;**9**:640925. DOI: 10.3389/fphy.2021.640925

[34] Okano N, Ishii A. Analysis of divided society at the standpoint of in-group and out-group using opinion dynamics. In: The procedings of IntelliSys 2021 Switzerland: Springer Nature; 2021

### **Chapter 10**

## Nigerian Press Coverage of Hate Speeches in the *Daily Trust, The Nation* and *The Guardian* Newspapers

*Aondover Eric Msughter*

### **Abstract**

In Nigeria, as well as in modern democratic nations, the press has always functioned as a tool for disseminating information on public affairs, interpreting government policies and programs, and providing a good platform to engage the citizens for discussion on issues affecting society. The media play a powerful role as intermediaries between political leaders and the public. The variables of frequency, location, direction, and journalistic genre were used in the study. Within this context, the study adopts content analysis. The study employs Lazarsfeld and Katz's Two-Step Flow and Castells' Theory of Network Society as theoretical framework. The study uses stratified sampling by days of the week and coding sheet as a method of data collection. The study found that the manifestation of hate speech was frequent in the 2015 general election. The study also found that the manifestation of hate speech had an overbearing on political news by the selected newspapers in the 2015 general election in Nigeria. The study concludes that such publications (hate speech) tend to make electorates have a different connotation to a candidate.

**Keywords:** *Daily Trust*, Hate Speech, *The Guardian*, *The Nation*, Nigeria

### **1. Introduction**

Universally, the press and politics are generally believed to enjoy a symbiotic relationship. In Nigeria, as well as in modern democratic nations, the press has always functioned as a tool for disseminating information on public affairs, interpreting government policies and programs, and providing a good platform to engage the citizens for discussion on issues affecting society. The media play a powerful role as intermediaries between political leaders and the public [1]. Xinkum in Suleiman and Owolabi [1] note that the role of the press becomes important, especially in influencing voters' judgments about the candidates and taking an informed decision about them. This perhaps explains why media scholars have accepted the economic and political changes in society [2].

Up till 1922, the election of public office holders was solely determined by the British colonialists. However, the Clifford Constitution altered the democratic process in the Nigerian political space as Nigerians were given the opportunity to vote and be voted for in the House of parliament. Realizing the role of the media in the democratic process is why a good number of the pre-independence political parties had a newspaper as an ally, which was considered imperative to the survival of their organization [2]. Retrospectively, since 1960, when Nigeria gained its independence from the British colonial ruler, to date, various parliamentary, military, and presidential systems of government have existed. In a democratic society, elections are mostly the conventional means of electing people into all political offices in the country. Against this background, Oso [2] observed that the importance attached to the party's newspaper was so enormous that people believed that party organizations were built around the press, rather than around organized members.

In line with Oso's view, the newspaper with its close link to political parties was used to set the political agenda. Newspaper like *Lagos Daily News* (1925) was established by Herbert Macaulay, who formed the Nigeria National Democratic Party (NNDP). Nnamdi Azikwe also used the *West African Pilot* (1937) to propagate the evangelism of NCNC in which he was a key stakeholder. Obafemi Awolowo also floated the *Nigeria Tribune,* which had a close link with the Action Group (AG). In the North, the *Northern People's Congress,* in 1949, took over Hausa language newspaper, *Gaskiya Ta fi Kwabo,* and its English language counterpart, *Nigerian Citizen* (later as *New Nigerian*), to advocate, defend, and advance its interest. The Federal government, under the Northern Peoples' Congress (NPC), established the *Morning and Sunday Post;* the Eastern Region (under NCNC) had the *Eastern Outlook,* while the North controlled *Gaskiya* and the *Nigerian Citizen.* Furthermore, Chief Samuel Ladoke Akintola established the *Morning Star* toward the end of his Premiership in the old Western Region.

With the intervention of the military in Nigerian politics on December 31, 1984, the Nigerian mass media witnessed the establishment of magazines, periodicals, and soft-sell newspapers. These include *The Newswatch, The News, The Tempo,* and *Tell* magazines. Others were indigenous language newspapers like *Alaroye, Gboungboun,* and *Irohin Yoruba.* The magazines in particular concerned themselves with investigative journalism, and they also contributed immensely toward constructive criticism and the democratization processes of the ruling military establishment under Babangida, Abacha, and Abdulsalam Abubakar, respectively. Ever since, the media have regarded the pursuit of full enthronement and sustenance of democracy and democratic institutions and good governance as its abiding responsibilities.

The Independent National Electoral Commission [3] report stated that consequent upon the approval of Saturday, March 28, 2015 as the date for the 2015 presidential and national assembly elections, the campaign exercise began full-blown. In that regard, 14 political parties and presidential candidates were approved by the Independent National Electoral Commission (INEC) in their news release. The parties included Action Alliance (AA), Allied Congress Party of Nigeria (ACPN), African Democratic Congress (ADC), All Progressive Congress (APC), Kowa Party (KP), The National Conscience Party (NCP), Peoples' Democratic Party (PDP), and Progressive People's Alliance (PPA), among others.

At the peak of the electioneering campaign, the two foremost parties (PDP) and (APC) went berserk by taking enmity to the extreme while maligning and attacking the personalities of each other's presidential aspirants through unbridled use of hate speeches. It became so bad that the entire campaign process was almost turned into a harvest of hatred and incitement of one party against the other instead of selling the individual party manifesto [4]. Within this context, this study examined the manifestation of hate speech in Nigeria.

*Nigerian Press Coverage of Hate Speeches in the* Daily Trust, The Nation *and* The Guardian*… DOI: http://dx.doi.org/10.5772/intechopen.108731*

### **2. Motivation of the study**

Hate speech is a globally endorsed paradigm, and the press, as an important institution in the democratic process, plays a key role during elections. As the Fourth Estate of the Realm, the press provides the platform for narratives and discourses in the service of elections, political negotiations, and other features of the contestations among politicians and other civil organizations involved in election administration. However, problems associated with election reporting and media role in political contestations and machinations, particularly on the African continent, have been a recurrent clog in the wheel of politics in Africa. For instance, in Nigeria, since the 1950s up to the early 1980s, spiraling into the Fourth Republic that started in 1999 and beyond, several election problems that were rooted in perceived mishandling of the electoral process by the media had occurred in the country. The 1965 parliamentary and 1983 general elections were faced by conflicts with accompanying widespread violence, which resulted in military interventions [5].

Apparently, the 2015 election was very keen to the extent that an alliance of opposition parties was formed to produce All Progressives Congress (APC) in a strong bid to dislodge the Peoples Democratic Party (PDP) that had been in power since 1999. Findings from the monitoring of the media coverage of these elections showed that there were cases of sponsorship of hate advertorials by the then Ekiti State governor, Ayodele Fayose, who, on January 19, 2015, ran adverts on the front pages of national dailies such as The *Daily Sun*, *The Guardian,* and *The Punch* titled "Nigeria Be Warned". In the advert, satirical reference was made to Buhari, the presidential candidate of the APC, that given his age and speculated illness and frail nature, he might die in office should he win, according to *Sahara Reporters* of January 19, 2015.

Incidentally, Section 95 of the Electoral Act 2010 disapproves of hate campaigns by stipulating that: (1) A political campaign or slogan shall not be tainted with abusive language directly or indirectly likely to injure religious, ethnic, tribal, or sectional feelings. (2) Abusive, intemperate, slanderous, or base language or insinuations or innuendoes designed or likely to provoke violent reactions or emotions shall not be employed or used in political campaigns. Yet, there were other instances of lack of discretion on the part of the media in the countdown to the 2015 and 2019 elections, in terms of inappropriate language use and inciting headlines. This was evident in the outcome of the monitoring of 12 national newspapers like *Daily Trust*, *The Nation*, *The Sun*, *The Punch*, *The Guardian*, *Vanguard*, *Daily Independent*, *National Mirror*, *Leadership*, *Nigerian Tribune*, *ThisDay*, and *Daily Champion* [6].

Findings by IPC [7] revealed that stories capable of inciting one section against the other were recorded 45 times during this monitoring period, while hate speech featured 8 times despite these provisions. A total of 117 reports were recorded in these categories in the six-month period at an average of about 20 per month across the 12 selected national print media. The documented inciting headlines also include the following: APC presidential candidate is a fundamentalist—Clarke (*ThisDay*, Jan. 17, 2015, page 15); will you allow history to repeat history itself? Enough of state burials (*Daily Sun*, Jan. 19, 2015, page 1); we are set for war—PAC (*Nigerian Tribune*, November 22, 2019), among others. Given this scenario, it is important to undertake a study on Nigerian press coverage of hate speeches in the *Daily Trust, The Nation,* and *The Guardian* newspapers.

### **3. The basic tool of scientific inquiry**

The problem statement informed the basic tool of scientific inquiry in this study as follows:


### **4. Literature review**

In relation to the literature, the study observed that the media did not comply with the code of ethics in publishing and broadcasting advertorials, while hate speech and inciting statements especially by the two major political parties (PDP) and (APC) were used in the media. As a result of the influence of advertising as a source of revenue, owners of newspaper businesses did not subject adverts to necessary checks. The existing literature presupposes that newspapers' coverage of national elections in Nigeria often promotes ethnic, regional, and religious interests. Theoretically, exponents of The Functional Theory of Campaign Discourse argue that the functional theory of campaign discourse renders a helpful scheme to classify and synthesize political advertising. They add that elections are intrinsically competitive; political actors deploy campaign messages that include advertising to present a more preferable image of them. They use political ads to acclaim themselves, positive statements about their credentials as the better candidate; attack an opponent's credentials; or defend with reputations against an opponents' attack through media platforms.

This supports the literature argument [1] that newspaper coverage of general elections and newspapers owned by the leaders of different political parties published negative reports on the opponents and their ethnic groups. In addition, comments deemed as offensive and employing hate speech, threats, abusive language, and assassination of character are published by the media. Corroborating, Ogbuoshi *et al.* [8] observed that hate speech is now a common phenomenon in present day society, and it is mostly made to achieve some sinister goals.

In this repeatedly corroborated incident of hate speech, Critical Race Theory explains the contexts of media use of phrases sponsored by politicians that refer to other opposition groups from descriptions that are not merely rhetorical but also pedestals on which hate speech flourishes. Durkheim's Social Fact and Weber's Social Action or Relations Theory depict that social reality focused attention on individualistic autonomy in terms of ideas and desires vis-à-vis social regularity to achieve sinister goals of hate speech in society.

Similarly, the existing literature attests that hate speech has become more vivid in the successive democratic dispensation than the previous ones, thereby keeping the citizens more divided, as hate speech is now the focal point and the instrument of campaigns. Thus, the parade of hate speeches in several newspapers analyzed showed that the media was used by politicians to stoke up hatred and stimulate violence among ethnic and political groups during the electioneering periods. Critics of Critical Discourse Analysis Theory argue that neutral representations are opposed to ideological representations, which are deemed to 'distort reality. Ideology is, accordingly, conceptualized in negative terms, as the opposite of 'truth',

### *Nigerian Press Coverage of Hate Speeches in the* Daily Trust, The Nation *and* The Guardian*… DOI: http://dx.doi.org/10.5772/intechopen.108731*

which systematically connotes how hate speech and language, dialects, and acceptable statements are used in a particular medium across different audiences.

The trend of discussion in the literature is disturbing, as scholars corroborated that commentators employ the use of hate language, verbal assault, name-calling, insults, and derogatory words to describe subjects. In relation to the above, this study armed with Katz and Lazarsfeld's Two-Step Flow theory, which asserts that information from the media moves in two distinct stages. First, individuals (opinion leaders) who pay close attention to the mass media and its messages receive the information. Opinion leaders pass on their own interpretations in addition to the actual media content. The reviewed literature also underscores the findings by the Centre for Information Technology and Development (CITAD) [9] that in the last election in Nigeria, instances of hate speeches were seen on conventional and social media. Largely on conventional media, the speeches were broadcast on certain television stations and published in some newspapers as well.

This coalesces with Castells' Theory of Network Society, which examines the concept of the network to a high level of abstraction, utilizing it as a concept that depicts macro-level tendencies associated with the social organization in informational capitalism. The role of networks in social theory is apt as follows: dominant functions and processes in the information age that are increasingly organized around networks. Within this context, this study examines Nigerian press coverage of hate speeches in the *Daily Trust, The Nation,* and *The Guardian* newspapers.

### **5. Theoretical framework**

The study adopted Lazarsfeld and Katz's Two-Step Flow and Castells' Theory of Network Society Theories. Lazarsfeld and Katz's Two-Step Flow was first introduced by Lazarsfeld et al. in 1944 to study the process of decision-making during a presidential election campaign. The study found empirical support for the direct influence of media messages on voting intentions. Armed with this data, Katz and Lazarsfeld developed the Two-Step Flow theory of mass communication. This theory asserts that information from the media moves in two distinct stages. First, individuals (opinion leaders) who pay close attention to the mass media and its messages receive the information. Opinion leaders pass on their interpretations in addition to the actual media content. The term 'personal influence' was coined to refer to the process of intervening between the media's direct message and the audience's ultimate reaction to that message. Opinion leaders are quite influential in getting people to change their attitudes and behaviors and are quite similar to those they influence. The Two-Step Flow theory has improved the understanding of how the mass media influence decision-making.

The theory refined the ability to predict the influence of media messages on audience behavior, and it helped explain why certain media campaigns may have failed to alter audience attitudes or behavior. The Two-Step Flow theory gave way to the multi-step flow theory of mass communication. Although the empirical methods behind the two-step flow of communication were not perfect, the theory did provide a very believable explanation for information flow. The opinion leaders do not replace media but rather guide discussions of media, which at times lead to issues of hate speeches. Lazarsfeld et al., in Hassan [10], discovered that most voters got their information about the candidates from other people who read about the campaign in the newspapers, not directly from the media. They concluded that word-of-mouth transmission of information plays an important role in the communication process and that mass media have only a limited influence on most individuals. Since opinion leaders pass on their interpretations in addition to the

actual media content, the manifestation of hate speeches on the pages of newspapers and how the opinion leaders tag meaning to words in Nigeria, like Gandollar instead of Ganduje, would affect the electoral victory when such interpretations are in a negative direction.

Castells' Theory of Network Society examines the concept of the network to a high level of abstraction, utilizing it as a concept that depicts macro-level tendencies associated with the social organization in informational capitalism. He expressed the role of networks in social theory as follows: dominant functions and processes in the information age are increasingly organized around networks. Networks constitute the hate speech morphology in societies, and the diffusion of networking logic substantially modifies the operation and outcomes in processes of production, experience, power, and culture. Understanding the societal context of such networks entails returning to the political economy of the social transformation of capitalist society. An analytical concept network is abstract and thus unable to frame the interpretation of real-life networks, whereas theoretical concept network is an excellent crystallization of the social morphology of informational capitalism [11].

As an upshot of the latter, the concept of network society has a certain intellectual appeal, even if it looks almost as if the formal description of the concept of the network was needed only to legitimate its use as a metaphor. Concerning the hardcore of the metaphor, the study comes to the true message of Castellsian political economy (where politicians metaphorically used negative words to refer to other opposition), and the network in its paradigmatic form is about the nodes and connections of powerful financial and economic institutions, which allow the flows of values in pursuit of the newspapers' accumulation of capital. This implies that 'network' in Castells' social theory is not an analytical concept but rather a powerful metaphor that served to capture the new social morphology of the capitalist system. In this context, the morphological manifestation of hate speech in the discourse of information society gains its momentum; it went out of intellectual fashion as well as political agenda and gave its place to the visions of the creative and or smart society. For instance, in Nigeria, the phrase 'change begins with me' is often used metaphorically and polemical.

Although the critics, who looked at the theories of the information society suspiciously as ideological constructs, created for political decisions, rather than instruments for understanding the social reality. Therefore, Castells believes that McLuhan's dictum, "the medium is the message," could be adequately applied in the way hate speeches flourish in newspapers' content. In this perspective, there is a network (politicians and newspaper organizations) that often creates a powerful metaphor that aptly portrays hate speech as a social morphology of information capitalism [12].

### **6. Research methodology**

The study employed content analysis as a method of data generation. Content analysis is an approach used in social science to examine the manifest content of media messages. According to NPC [13], three hundred and ten Nigerian newspapers exist in the country. Therefore, the population of the study constitutes the 310 newspapers in Nigeria. The sampling technique is stratified sampling. Since the sampling technique is stratified sampling by days of the week, it means that the three newspapers under investigation formed the sample size of the study. Below are the sample editions that were studied from the three newspapers:

*Nigerian Press Coverage of Hate Speeches in the* Daily Trust, The Nation *and* The Guardian*… DOI: http://dx.doi.org/10.5772/intechopen.108731*

January Editions: (2, 5, 8, 11, 14, 17, 20, 23, 26,) = 9 days. February Editions: (2, 5, 8, 11, 14, 17, 20, 23, 26,) = 9 days. March Editions: (2, 5, 8, 11, 14, 17, 20, 23, 26,) = 9 days. April Editions: (2, 5, 8, 11, 14, 17, 20, 23, 26,) = 9 days. May Editions: (2, 5, 8, 11, 14, 17, 20, 23, 26,) = 9 days. June Editions: (2, 5, 8, 11, 14, 17, 20, 23, 26,) = 9 days.

The sampling interval starts from the second edition of each month, as January has 31 days, February 28, March 31, April 29, May 31, and June 30. Therefore, the scale for rating the sampling is as follows: (2) + 3 = (5) + 3 = (8) + 3 = (11) + 3 = (14) + 3 = (17) + 3 = (20) + 3 = (23) + 3 = (26) in all the months. This means two months were selected before the 2015 general election, two months during the 2015 general election, and two months after the 2015 general election to determine the manifestation of hate speech by the three newspapers.

The papers are selected because they are among the 12 national papers, which means they share certain characteristics. The study considered the following units of analysis: political news, editorial, cartoons, and advertorial.


The content categorization is based on the indicators that are used to identify what constitutes hate speech like offensive, hateful, incisive, pungent, and sarcasm as developed by [11, 14] and moderated by the current study. These forms of hate speech were read and carefully placed into the following categories:


The data gathering instrument in this study is a coding sheet. Coding is a visible surface in a text; for example, the researcher counts the number of times or phrases that appear in a written text. The study adopted content validity whereby experts in the field of communication ascertained the comprehensiveness and adequacy of the coding sheet [11]. Two coders were trained and trusted to code the selected editions. Data generated were presented using cross-tabulation, frequency, and percentages.

### **7. Findings and discussion**

**Table 1** examines the frequency of hate speech in the 2015 general election by the selected newspapers. Based on the data, the manifestation of hate speech in the 2015 by *Daily Trust* accounts for 20% (n = 67) offensive, 24.2% (n = 81) hateful, 17.3% (n = 58) incentive, 15.5% (n = 52) pungent, and 22.10% (n = 77) sarcasm. *The Nation* has 20.9% (n = 57) offensive, 24.3% (n = 66) hateful, 14.3% (n = 39) incentive, 21.3% (n = 58) pungent, and 19.1% (n = 52) sarcasm. *The Guardian* records 18.2% (n = 65) offensive, 27.5% (n = 98) hateful, 15.2% (n = 54) incentive, 17.7% (n = 63) pungent, and 21.3% (n = 76) sarcasm. Cumulatively, the manifestation of hate speech in the *Daily Trust, The Nation,* and *The Guardian* newspapers are as follows: 19.6% (n = 189) offensive, 25.4% (n = 245) hateful, 15.7% (n = 151) incentive, 17.10% (n = 173) pungent, and 21.3% (n = 205) sarcasm. The data indicate that the manifestation of hate speech was more frequent in *The Guardian* in the 2015 general election, followed by the *Daily Trust* newspaper. Based on the content categorization, hateful speeches were dominant compared to other categories like offensive, incentive, pungent, and sarcasm in the 2015 general election.

**Table 2** shows the independent sample statistics of 2015 frequency of hate speech (FQHS). The FQHS mean of 2015 (64.20) is significantly high. This indicates that in the selected newspapers, hate speech in the 2015 general election was very high, which validates the findings in **Table 1** above. The IPC report [7] also supported the findings that many of the news reports at the 2015 presidential


### **Table 1.**

*Frequency of hate speech in the 2015 general election.*


### **Table 2.**

*Independent samples statistics of 2015 frequency of hate speech.*

*Nigerian Press Coverage of Hate Speeches in the* Daily Trust, The Nation *and* The Guardian*… DOI: http://dx.doi.org/10.5772/intechopen.108731*


**Table 3.**

*Dominant location for the placement of stories with hate speech in the 2015 general election.*

campaign had dangerous and outrageous headlines. Some of the statements were largely disparaging, while a great number turned out to be a figment of the imagination of politicians. Stories capable of inciting one section of the nation against the other were recorded forty-five (45) times during the 2015 presidential campaign.

**Table 3** ascertains the dominant location for the placement of stories with hate speech in the 2015 general election by the selected newspapers. The rating scale of the front page, inside page, and back pages was used to determine the manifestation of hate speech in the 2015 general election. The data show that in the 2015 general elections, *Daily Trust* has 17.6% (n = 59) stories that contained hate speech on the front page, 79.1% (n = 265) on the inside page, and 3.3% (n = 11) on the back page. *The Nation* accounts for 17.6% (n = 48) stories with hate speech on the front page, 79.8% (n = 217) on the inside page, and 2.6% (n = 7) on the back page.

Similarly, *The Guardian* records 11.8% (n = 42) stories that contained hate speech on the front page, 83.4% (n = 297) on the inside page, and 4.8% (n = 17) on the back page. Cumulatively, in 2015, 15.5% (n = 149) are on the front page, 80.9% (n = 779) on the inside page, and 3.6% (n = 35) on the back page. Based on the result, the manifestation of hate speech by the selected newspapers in 2015 appears more on the inside pages than on front and back pages.

**Table 4** shows the independent sample statistics of 2015 dominant locations for the placement of stories with hate speech (DOML). The DOML mean of 2015 (107.00) is very high. The result is concomitant with the findings in **Table 3**. In another corroborated literature, (CITAD) [9] found that in the last election in Nigeria, instances of hate speeches were seen on conventional and social media. Largely on conventional media, the speeches were broadcast on certain television stations and published in some newspapers as well. In this repeatedly corroborated incident of hate speech in the selected newspapers, Castells' Theory of Network Society examines the concept of the network to a high level of abstraction, utilizing it as a concept that depicts macro-level tendencies associated with the social organization in informational capitalism. He expressed the role of networks in social theory as follows: dominant functions and processes in the information age are increasingly organized around networks where issues of hate speech are dominant.


### **Table 4.**

*Independent samples statistics of 2015 dominant location for the placement of stories with hate speech.*


### **Table 5.**

*Direction of stories on hate speech in the 2015 general election.*

**Table 5** identified the direction of stories on hate speech in the 2015 general election by the selected newspapers. The data point that *Daily Trust* has 30.7% (n = 103) in the positive direction, 34.3% (n = 115) in the negative direction, while 34.9% (n = 117) were in the neutral direction. *The Nation* has 27.2% (n = 74) in the positive direction, 35.7% (n = 97) in the negative direction, and 37.1% (n = 101) in the neutral direction. Furthermore, *The Guardian* has 31.5% (n = 112) in the positive direction, 35.4% (n = 126) in the negative direction, and 33.1% (n = 118) in the neutral direction. Cumulatively, 30.0% (n = 289) was in the positive direction, 35.1% (n = 338) in the negative direction, and 34.9% (n = 336) in the neutral direction. The data show that the manifestation of hate speech by the selected newspapers was in the negative direction with 35.1% in the 2015 general election.

**Table 6** shows the independent sample statistics of 2015 direction of stories on hate speech (DIRS). The DIRS mean of 2015 (107.00) is significantly high. This validates the findings in **Table 5** that hate speech was in a negative direction in 2015. This supports the literature argument [15] that although quantitatively, positive comments dominate the study population, qualitatively, the trend of discussion is disturbing, as commentators employ the use of hate language, verbal assault, name-calling, insults, and derogatory words to describe subjects. For example, on the inside page of *The Nation* newspaper of Sunday, March 15, 2015, Patience Jonathan, former First Lady, said "*Anybody that come and tell you change (that is, the APC slogan), stone that person … What you did not do in 1985, is it now that old age has caught up with you that you want to come and change … You cannot change rather you will turn back to a baby*." Armed with the theoretical postulations of Katz and Lazarsfeld's Two-Step Flow theory, which asserts that information from the media moves in two distinct stages. First, individuals (opinion leaders) who pay close attention to the mass media and its messages receive the information. Opinion leaders pass on their interpretations in addition to the actual media content.

**Table 7** examines the journalistic genre in which hate speech in the 2015 general election appeared in the selected newspapers. Thus, in the 2015 general elections, *Daily Trust* has 85.1% (n = 285) on political news, 3.6% (n = 12) on editorial, 6.3% (n = 21) on cartoons, while 5.1% (n = 17) on advertorial. Similarly, *The Nation* has 84.9% (n = 231) on political news, 2.9% (n = 8) on editorial, 8.8% (n = 24) on cartoons, while 3.3% (n = 9) on advertorial. Also, *The Guardian* has 86.8% (n = 309)


### **Table 6.**

*Independent samples statistics of 2015 direction of stories on hate speech.*

*Nigerian Press Coverage of Hate Speeches in the* Daily Trust, The Nation *and* The Guardian*… DOI: http://dx.doi.org/10.5772/intechopen.108731*


### **Table 7.**

*Journalistic genre for hate speech in the 2015 general election.*


### **Table 8.**

*Independent samples statistics of 2015 journalistic genre used for hate speech.*

on political news, 2.5% (n = 9) on editorial, 5.9% (n = 21) on cartoons, and 4.8% (n = 17) on advertorial. In the overall journalistic genre, 85.7% (n = 825) was on political news, 3.0% (n = 29) was on editorial, 6.8% (n = 66) was on cartoons, and 4.5% (n = 43) was on advertorial. The data show that *The Guardian* accounts the highest in terms of political news with 86.8%, followed by *Daily Trust* with 85.1% and *The Nation* with 84.9%. This implies that in the 2015 general election, the manifestation of hate speech was on political news by the selected newspapers.

**Table 8** shows the independent sample statistics of the 2015 journalistic genres used for hate speech (JOUG). The JOUG mean of 2015 (80.25) is adequate. This corroborated the findings in **Table 7** that the manifestation of hate speech in the 2015 general election appear more on political news. Rasaq *et al.* [16] observed that hate speech was the focal point and the instrument of the campaign. Therefore, the parade of hate speeches in several newspapers analyzed showed that media was used by politicians to stoke up hatred and stimulate violence among ethnic and political groups during the electioneering periods as well as in daily life.

### **8. Conclusion**

The study examines Nigerian press coverage of hate speeches in the *Daily Trust, The Nation,* and *The Guardian* newspapers. The study found that the manifestation of hate speech is frequent in 2015 general election. Such speeches appear more in *The Guardian* in the 2015 general election, followed by *Daily Trust,* and *The Nation* newspaper has fewer stories that contain hate speeches within the period of the study. The study discovered that the manifestation of hate speech by the selected newspapers in the 2015 general election was significantly high on the inside pages than front and back pages. The findings of the study revealed that the manifestation of hate speech by the selected newspapers was in a negative direction in 2015. The study also found that the manifestation of hate speech had an overbearing on political news by the selected newspapers in the 2015 general election in Nigeria. The study concludes that such publications (hate speech) tend to make electorates have a different connotation to a candidate.

*The Psychology of Trust*

### **Author details**

Aondover Eric Msughter Department of Mass Communication, Caleb University, Lagos, Nigeria

\*Address all correspondence to: aondover7@gmail.com

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Nigerian Press Coverage of Hate Speeches in the* Daily Trust, The Nation *and* The Guardian*… DOI: http://dx.doi.org/10.5772/intechopen.108731*

### **References**

[1] Suleiman H, Owolabi E. Hate speech and its harms: A communicative perspective. Journal of Communication. 2018;**47**(1):4-19

[2] Oso L. Press and Politics in Nigeria: On whose Side? Lagos: LASU Inaugural Lecture series, Lagos State University; 2015

[3] Independent National Electoral Commission. Report on the 2015 and 2019 general elections. 2015

[4] The Punch. 2015 and 2019 General Elections in Nigeria. Kano, Nigeria: The Punch; 2017

[5] Popoola T. Parrot Journalism. A Professional Guide in Investigative Journalism. Lagos. Ethiopia: Diamond Publications Limited; 2019

[6] Arogundade L. Media and Elections: Professional Responsibilities of Journalists. Tentacle Communication: Lagos; 2019

[7] Election Reporting Manual in Nigeria: The Institute of War and Peace Reporting (IWPR) and Media Right Agenda (MRA) with the Support of USAID and IRI. Nigeria: International Press Centre; 2015

[8] Ogbuoshi LI, Oyeleke AS, Folorunsho OM, editors. Fake News and Hate Speech: Narratives of Political Instability. 6th ed. Concord Ontario, Canada: Canada University Press; 2019

[9] Centre for Information Technology and Development (CITAD). Hate Speech and the Campaigns for 2019 Elections. CITAD; 2018

[10] Hassan BS, Owolabi TO. Nigerian press coverage of hate speeches and negative campaigns in the 2015 presidential elections. Journal of

Communication and Media Research. 2020;**10**(1):52-62

[11] Alakali TT, Faga HP, Mbursa J. Audience perception of hate speech and foul language in the social media in Nigeria: Implications for morality and law. Academicus International Scientific Journal. 2017;**3**(2):161-177

[12] Doda MA. Introduction to Sociology. Ethiopia: Ethiopia Ministry of Education; 2015

[13] Nigeria Press Council. Newspaper and Magazine Distribution across Geopolitical Zones. Nigeria: Nigeria Press Council; 2020

[14] Auwal AM. Social media and hate speech: Analysis of comments on Biafra agitations, arewa youths' ultimatum and their implications on peaceful coexistence in Nigeria. MCC. 2018;**2**(1):54-74

[15] Lucas JM, Targema TS. Hate speech in readers' comments and the challenge of democratic consolidation in Nigeria: A critical analysis. Malaysian Journal of Media Studies. 2018;**20**(2):23-38

[16] Rasaq A, Udende P, Ibrahim A, Oba L. Media, politics, and hate speech: A critical discourse analysis. e-Academia Journal. 2017;**6**(1):240-252

### **Chapter 11**

## Trust in the Nonprofit Domain: Towards an Understanding of Public's Trust in Nonprofit Organizations

*Annika Becker*

### **Abstract**

Trust in the nonprofit domain has been subject to a large interest both among scholars and practitioners over the past few years. Today, we differentiate between a range of different forms of trust, namely, organizational and sectoral trust as well as more generalized and institutional trust. Another differentiation in nonprofit literature relates to the subject that forms trust towards a nonprofit organization, reflected by the strength of the individual-organizational-relationship. In that, two forms of trust, namely, a narrow form of relational trust and broader trust among the public have evolved. While previous research provides varying conceptual approaches for explaining public's trust in the nonprofit sector, most scholars, however, approach public trust from a rather narrow relationship management perspective. This chapter conceptualizes and operationalizes public trust from a broader perspective and emphasizes that to get public support to ultimately further their missions, nonprofit organizations should strive for building, maintaining, and restoring public's trust. This chapter accordingly presents five mechanisms that are associated with public's trust in nonprofit organizations: 1) promise of mission and values, 2) organizational reputation, 3) transparency and accountability, 4) performance and social impact, and 5) use of contributions. Thereby, recent trends in academic literature are identified—nonprofit branding and nonprofit accountability—that have great ability to address these mechanisms to successfully improve public trust. Results from this chapter provide nonprofit scholars with insights into a broader conceptualization and operationalization of public trust in nonprofit organizations, and with future research ideas. Nonprofit managers may benefit by gaining insights into how to sustainably improve trust among the general public by focusing on nonprofit branding and accountability strategies.

**Keywords:** public trust, nonprofit organization, nonprofit branding, nonprofit accountability

### **1. Introduction**

"Despite the diversity among NPOs, there is one thing that they have in common–*public trust* is their most valuable asset" ([1]: 265). In that, scholars have highlighted the nonprofit organization's dependency on the public's trust for legitimacy and support, and ultimately for fostering their organizational goals and missions [2, 3]. Notwithstanding the high importance of public trust for the continuation of nonprofit organizations [4, 5], corresponding research is scattered, and disparate associations have been found. For example, in a recent meta-analysis on trust and giving in the nonprofit domain, Chapman et al. [6] investigate to what extent trust is a prerequisite for giving to nonprofits. The authors confirmed a positive association between both concepts across diverse measures considering 69 effect sizes from 42 studies sampling 81,604 people in 31 countries. Although trust and giving are positively associated, the overall relationship is relatively modest in size, varying by the form of trust, e.g. organizational and sectoral trust are more important compared to generalized and institutional trust. As another point, the authors highlight the lack of experimental and longitudinal research, still leaving open "whether trust really is a prerequisite for or consequence of charitable giving" ([6], p. 18).

Moreover, most studies conceptualize the public's trust in nonprofit organizations primarily according to a "narrow" relationship management perspective. This perspective equates the general public with nonprofit stakeholders such as donors, volunteers, or public authorities that are directly related to the organization through actual experiences and transactions, and stronger relationships respectively. Bryce [2], for example, argues that "[t]he public's positive or negative experiences in core transactions with an organization may be the principal bases for the impairment or improvement of the public trust". To restore and improve public trust in nonprofit organizations, he accordingly suggests the use of relationship marketing concepts. Similarly, Sargeant and Lee [7] put public's trust at the core of a relational fundraising approach, even though the authors find empirical evidence that "trust may operate at two levels distinguishing donors from non-donors". However, the very same approaches to address both donor and public trust may not be reasonable.

This chapter calls into question former relationship-focused conceptualizations of public trust. The aim of this chapter is hence to move beyond the narrow trust perspective to conceptualize and operationalize public's trust in nonprofit organizations in accordance with a broader perspective. That is, the larger public had no or few actual transactions with the organization yet, and rather vague assumptions or interests based on initial points of contact such as through the media, word-ofmouth, or the organization's fundraising activities. In the case of a series of positive contact points, a stronger relationship might evolve subsequently at a later stage [8]. The nature of public's trust in nonprofit organizations hence depends upon few contact points between the public and the organization, which are embedded in a comparatively loose connection between those involved. To directly address these contact points, the current chapter suggests that nonprofit organizations can send signals through the implementation of branding and accountability strategies, rather than through relationship management approaches. These strategies arise from the broad trust perspective, and from recent trends in nonprofit trust literature that turned out to be most promising, also as strategies for restoring public's trust in the case of a scandal as we have seen them repetitively in the nonprofit domain over the past years. As such, they have ability to directly influence the mechanisms that are related to public's trust in nonprofit organizations.

To fully evolve, this chapter claims public trust to be associated with five mechanisms, including 1) promise of mission and values, 2) organizational reputation, 3) transparency and accountability, 4) performance and social impact, and 5) use of contributions. It follows that public trust depends on how well the organization performs relating to each of these fields that act as mechanisms for strengthening trust. In contrary, if the nonprofit organization blocks one or more of these mechanisms, it impairs this trust; and at its worst, a corresponding scandal is likely to be provoked. Both for the improvement and impairment of public's trust in nonprofit

organizations, this chapter provides nonprofit scholars and managers with insights into the mechanisms behind it, and provides strategies to successfully build, maintain, and restore public trust.

### **2. Perspectives and definition of public trust in nonprofit organizations**

The nonprofit organizations' very existence is assumed to be based on their greater trustworthiness. Nonprofit organizations are prohibited by law from distributing profits to private parties, and unlike their commercial counterparts, they do not have legal owners with residual claims [5, 9]. The nonprofit character accordingly provides signals of trust that help the public and other nonprofit stakeholders to overcome uncertainty caused by agency problems regarding the organizations' behavior and quality [4, 5, 10]. In view of some of the most recent nonprofit scandals (e.g. SOS-Children Villages or Oxfam's scandals of misconduct), scholars yet question the effectiveness of Hansmann's [9] nondistribution constraint alone to mitigate these scandals' effects [10]. Where the nonprofit character by itself cannot offer assurance regarding the organizations' good intentions, and the public has difficulties assessing the organizations trustworthiness, additional trust signals are vital [2, 11, 12].

According to the narrow perspective, these signals primarily refer to relationship-based management, marketing, and fundraising measures that are suitable to target stakeholders such as donors, or volunteers within a stronger relationship. Bryce [2] suggests sending a series of relationship messages, for example, with the purpose of affirming the ability to make discretionary decisions regarding the use of contributions, or communicating realizable future performances. As such, the narrow perspective assumes a stronger transactional relationship between the public and the organization, expecting the public to be susceptible to these messages. Although someone who has already donated to an organization is expected to value messages on how his or her donation is used, this chapter questions the larger public to be susceptible to corresponding messages. According to the broad perspective, the larger public rather relies on general cues or signals that may be derived from an organization's self-assessments, statements relating to the organizational mission and values as well as fundraising activities, annual reports, or websites. Third-party organizations such as watchdogs and funding agencies, or even word-of-mouth, and the media can provide additional signals to inform the public's assessments of the organization's trustworthiness [13, 14]. It follows that nonprofit organizations, in turn, must be able to identify and communicate trust building signals to stakeholders and the larger public to cultivate trust within their network of relationships [12]. See **Table 1** for a comparison of both perspectives on public's trust in nonprofit organizations.

Within this context, scholars have defined public's trust in nonprofit organizations mainly in accordance with a rather narrow trust perspective, and relating to strong stakeholder relationships (e.g., [1, 2, 7]). They accordingly refer to trust as a two-dimensional construct. The first dimension refers to generally positive trustrelated expectations, or specific characteristics of the trustee (the nonprofit organization), such as its ability, benevolence, and integrity. Considering the special features of organizations from the nonprofit sector, the benevolence dimension is particularly dominant in this domain [16, 17]. The second dimension refers to the (nonprofit) stakeholder's willingness to accept vulnerability, which comes with an element of risk [18]. According to the broad perspective, public trust, however, evolves in the context of weak relationships between organizations and the larger public, based on initial points of contact. Such contact points may sufficiently inform the public's assessments of the organization's general trustworthiness, yet,


### **Table 1.**

*Perspectives on public Trust in Nonprofit Organizations.*

do not contain major elements of risk. For example, if an individual from the larger public derives information from an organization's website, this may shape the individual's first opinion on the organization's trustworthiness but he or she does rather face no or a weak risk at this point of (weak) relational involvement with the organization. Therefore, this chapter draws on a definition highlighted by Becker et al. [15], that builds on Morgan and Hunt's conceptualization ([19]: 23) to explicitly focus on the first dimension, and conceptualize public trust as "existing when one party has confidence in an exchange partner's reliability and integrity". Public trust is hence considered an aggregate of each interaction between an individual and the organization, which further reflects the overall public attitude towards an organization [15, 20].

### **3. Five mechanisms associated with public trust**

Based on an extensive literature review as well as former trust conceptualizations (e.g., [2]), this chapter presents five mechanisms that are associated with public's trust in nonprofit organizations. The mechanisms relate to fundamental principles and special features of nonprofit organizations, and corresponding processes in the sector. Following all five mechanisms are explained in detail. That is, the mechanisms' bases for the development of public trust as well as managerial actions that potentially impair public trust are presented. **Table 2** illustrates the mechanisms in an overview.

### **3.1 Promise of mission and values**

Promise of mission and values is the first mechanism that is associated with public's trust in nonprofit organizations. An organization's mission refers to the organization's long-term objective and determines its strategic direction [21], and is thus also relevant to public trust [2, 7, 22]. Values further range from ethical responsibilities to competitive values, and specify how an organization conducts its activities and strategies [23]. In the nonprofit sector values such as altruism, humanity, equality, helpfulness, but also trustworthiness and honesty are prominent [23, 24], having distinct impacts of public's trust. Both missions and values can vary considerably across organizations, with substantially different meanings and


*Trust in the Nonprofit Domain: Towards an Understanding of Public's Trust… DOI: http://dx.doi.org/10.5772/intechopen.100636*

### **Table 2.**

*Five Mechanisms that are Associated with Public Trust in Nonprofit Organizations.*

relevance for the larger public as well as other stakeholders [14, 25]. For example, Oxfam states its organizational mission, as follows "We fight inequality to end poverty and injustice.", and "commit[s] to living [their] values [in particular, equality, empowerment, solidarity, inclusiveness, accountability, courage] so that [they] can be known for [their] integrity. This means transforming [their] governance, management, and operational structures, and nurturing a culture of continuous learning and reflection" [26]. The principal basis for public trust relates to the organization's adherence to act according to its organizational mission and values. If organizations, however, violate or misrepresent these, public trust is impaired [2]. Also, a lack of clarity in expressions of mission statements and values may impair public trust such that the public perceive nonprofit managers as insincere about their true goals, and therefore assess the organization's trustworthiness as significantly lower [27].

### **3.2 Organizational reputation**

The organizational reputation constitutes the second mechanism that is associated with public's trust in nonprofit organizations. Organizational reputation, namely the collectively held mental image of the organization [28, 29], is considered a highly important intangible asset in nonprofit organizations [30]. It consists of

different mental images across various stakeholder groups that can vary highly depending on which assessments are gathered. In view of recent nonprofit scandals, the reputation of nonprofit organizations has been tremendously threatened because it is influenced through monitoring problems. According to Prakash and Gugerty [10], "[i]t is not an exaggeration to say that the negative reputational effects of a few 'bad apples' are beginning to undermine the reputation of the sector as a whole", and the organizational reputation has distinct impacts on public trust [31]. In the nonprofit sector, reputation is conceptualized primarily with respect to the organization's competences and its likeability that accordingly acts as a basis for public trust [29]. If an organization, in turn, cannot maintain its images as sufficiently competent and likeable across a variety of people, public trust is impaired.

### **3.3 Transparency and accountability**

Transparency and accountability represent the third mechanism that is related to public trust. Its importance is based on the fact that in the nonprofit domain organizations are – dependent on the home countries' varying regulations – are more or less not obliged to comprehensively report financial and non-financial information publicly. However, we know about the importance of transparency and accountability standards in the sector that is vital to improve public trust [32–34]. That is, nonprofit stakeholders and the larger public face uncertainty because they cannot easily observe the organization's project and operational expenses, and so its behavior and the quality of services [10]. It follows that high transparency and compliance with transparency and accountability standards build an essential basis for public trust [10, 34, 35]. This basis is threatened through organizations that lack transparency, or (at its worst) do not comply with legal accountability standards and requirements.

### **3.4 Performance and social impact**

The organization's performance and social impact represent the fourth mechanism that improves public trust. Nonprofit organizations often provide services that are highly intangible and of which the quality is difficult to observe [16]. The organization's performance in the form of financial, stakeholder, market, and mission performance is hence difficult to verify both for contributors and beneficiaries, and even more so, for the larger public [14]. Achieving and measuring actual impacts has been found to be increasingly important for organizations and their contributors; yet, social impact measurement is still in its infancy, and few organizations have capacities for accordant evaluations [36]. Despite agency problems regarding the organizations' performances and social impacts, they form the basis to ultimately further the mission. It follows that organizational performance (and to a growing extent, also social impact) are particularly relevant for public's trust. Impairments of public trust accordingly include organizational mal-performance [2], and no social impact.

### **3.5 Use of contributions**

The use of contributions is the fifth mechanism that is associated to public's trust in nonprofit organizations. That is, the majority of nonprofit organizations rely on external funding (for example, from private and corporate donors, or public authorities and foundations) to finance the organization's project and operating expenses, to ultimately ensure the organization's continuation. The principal basis for improving public trust according to this mechanism is the mission-based use as

*Trust in the Nonprofit Domain: Towards an Understanding of Public's Trust… DOI: http://dx.doi.org/10.5772/intechopen.100636*

well as discretion in the handling of contributions, and its preservation. On the other hand, trust is impaired through managerial actions such as misuse, misrepresentation, negligence, and imprudence in the handling of donations and other contributions [2, 37]. In the past, the unreasonable use of contributions have been particular serious in some cases, and subsequently resulted in a nonprofit scandal that affected not only involved organizations, but questioned the legitimacy also of other organizations in the nonprofit sector. For example, in 2014, Greenpeace International's use of contributions created a scandal because an employee of the organization used large amounts of donated funds for foreign exchange trading [38]. In contrary, it is assumed that nonprofits clearly stating their use of contributions exhibit higher levels of trustworthiness. Some organizations recently started to develop new marketing and fundraising models around this topic. For example, the nonprofit organization *charity: water*, committed to bring clean and safe drinking water to people in developing countries, relies on private donors to fund all overhead costs, so 100% of public donations go directly to fund clean water projects [39].

### **4. Operationalization of public trust**

Pursuant to conceptualizations of the narrow relationship management perspective, scholars rarely distinguish between the larger public and other external stakeholder groups in their operationalizations of public trust. In their study on public's trust in nonprofit organizations, Sargeant and Lee [7] yet found empirical evidence indicating that donors place significantly more trust in charitable organizations than non-donors. Because only few operationalizations and measurement approaches explicitly focus on public trust, this chapter involves also those focusing on donor trust. **Table 3** shows the prevailing trust measurement scales in the nonprofit sector.

The existing operationalizations and measurement approaches relating to (public) trust in nonprofit organizations can be divided into two categories. The first category refers to second-order trust operationalizations, and few scholars operationalize trust in the nonprofit sector by means of second-order-constructs (e.g., [45, 46]). Corresponding operationalizations come from the narrow relationship management perspective such that they focus on trust emerging from stronger relationships between donors and nonprofit organizations. For example, Sargeant and Lee [45, 46] operationalize donor trust with respect to four components: 1) relationship investment, 2) mutual influence, 3) forbearance from opportunism, and 4) communication acceptance. The authors claim this operationalization of trust only to be relevant "in the context of a donor's relationship with a specific organization" ([45]: 618) as the dimensions are based on an existing donororganization-relationship. The respective first-order dimensions show sufficient high values of Cronbach's alpha, and average variance extracted, exceeding the respective thresholds of .70, and of .50 respectively [40, 43]. It is important to note that the four dimensions do not include any of the two trust dimensions (trustworthiness of NPO and risk for donors), given that the authors rather identified "key behaviors indicative of the presence [of trust]" ([7]: 616).

The second category relates to scale measurement approaches of trust in the nonprofit sector that directly address the trust concept as outlined in this chapter. Most studies fall into this category, and either measure trust according to a narrow or a broad perspective (e.g., [8, 17, 41, 47]). That is, most measurement scales seek to measure donor trust, whereas one prevailing measurement scale is used both in the context of donor and public trust. All scales exhibit sufficient psychometric



3. I would trust this NPO to use donated funds appropriately.


### **Table 3.**

*Operationalizations and measurement approaches of public Trust in Nonprofit Organizations.*

properties. The measures explicitly focusing on donor trust emerge from the narrow perspective, such that they include the first dimension of trust, measuring the organization's trustworthiness; to a lesser extent, they also include the risk dimension [17, 47]. The measures to operationalize both donor and public trust have been used in two ways: They include either the measurement items (1)–(3) [41], or all items (1)–(5), which specify additional donor and fundraising aspects [7, 8]. The latter rather emerges from a narrow perspective, and more strongly focuses on trust in the context of donor and fundraising issues. As such, the measure also refers to the potential risk of donors [7, 8]. In contrast, Sargeant and Woodliffe's [41] scale includes the measurement items (1)–(3). The scale explicitly focuses on the first trust dimension, such that corresponding items target the nonprofit organization's trustworthiness, and relate to weaker relationships between organizations and the public. Against this background, and in accordance with the broader perspective, this chapter suggests that Sargeant and Woodliffe's scale is particularly suitable for operationalizing public trust. However, these items still do not address all mechanisms that are associated with public's trust, and the accordant measurement scale is therefore capable of improvement (see future research ideas).

### **5. Nonprofit management strategies to improve public trust**

To build and maintain public's trust in nonprofit organizations, this chapter claims strategies from the field of nonprofit branding as well as nonprofit accountability to be of great significance. They are also suitable for restoring public trust, if managerial action has led to its impairment. Of particular importance are these strategies in the case of nonprofit scandals. One the one hand, they can help involved nonprofit organizations to recover from scandals. On the other hand, they have great ability to protect other nonprofit organizations from negative spillover effects in the sector. The underlying rationale of the functioning of these strategies is that external stakeholders face uncertainty regarding the organization's trustworthiness [10], and they "seek assurances beyond those provided by public regulations that organizations are behaving responsibly, following societal expectations and

norms of behavior" ([13]: 1). This is where strategies of nonprofit branding and nonprofit accountability provide assurance for the public, attesting the organization's trustworthiness [44, 48].

The first strategy of improving public's trust in nonprofit organizations refers to the field of nonprofit branding. Precisely, the nonprofit brand equals a "shortcut" that provides the general public with valuable information about the nonprofit organization ([49]: 22). In particular, the brand's signaling function enables organizations to spread signals relating to the organization's mission and core values [49, 50]. It thus has the ability to clearly inform the public's assessments of the organization's trustworthiness with respect to its mission and values as well as its performance. Moreover, branding strategies can effectively target the various mental images of nonprofit stakeholders, to successfully build up a high organizational reputation. A strong brand ultimately has the potential to act as an additional safeguard and reinforcement to the public along with the nondistribution constraint, which may represent a seal of trust [51]. For Sargeant [8], nonprofit brands "are in essence a promise to the public that an organization possesses certain features or will behave in certain ways". In this line, Laidler-Kylander and Stenzel [49] "believe that the brand is the vehicle for building this trust". A strong nonprofit brand can accordingly protect the respective organization against negative spillover effects caused by other nonprofit organizations, and they are less susceptible to risk [51]. In their prominent article "The Role of Brand in the Nonprofit Sector", Kylander and Stone [52] share their results evaluating the brand of one of the biggest nonprofit organizations worldwide, the World Wildlife Fund (WWF), citing Marsh, COO of the WWF, as follows "Our brand is the single greatest asset that our network has, and it's what keeps everyone together" ([52], p. 5).

The second strategy of improving public's trust in nonprofit organizations arises from the field of nonprofit accountability. Nonprofit accountability and governance programs and initiatives aim to develop common standards across nonprofit organizations to support good governance in nonprofit sectors worldwide. In particular, voluntary nonprofit accountability in the form of various codes of conduct, selfregulation mechanisms, and certification and accreditation schemes has great potential to improve and restore public's trust in nonprofit organizations [10, 32, 35, 48, 53]. Slatten et al. [48] argue that "the adoption of standards for ethical and accountable behavior may provide the solution [to the climate of shaken public trust in the non-profit sector]". First empirical evidence shows that voluntary accountability, and externally certified accountability (including accreditation systems), can enhance public trust in nonprofit organizations [32, 53]. It follows that organizations increasingly devote efforts to demonstrating their trustworthiness with various seals and certifications [2, 34, 51]. Precisely, voluntary nonprofit accountability strategies address the trust-driving mechanisms by their ability to signal adherence to the organization's mission and core values, and regarding the quality of organizational performance [32]. These strategies further contribute to the organizational reputation by joining high-reputational initiatives [13], and they particularly strengthen compliance with certain transparency and accountability standards, also through (external) certifications that attest the organization's adequate use of contributions [37, 53].

### **6. Future research ideas**

This chapter also suggests directions for further research regarding public trust in nonprofit organizations. First, although a number of scholars agree that public's trust in (charitable) nonprofit organizations is under increasing pressure (mainly

*Trust in the Nonprofit Domain: Towards an Understanding of Public's Trust… DOI: http://dx.doi.org/10.5772/intechopen.100636*

caused by public scandals and commercialization issues) [54, 55], other scholars find no empirical evidence for decreased public trust and confidence in the nonprofit sector (e.g., [56]). When related to the important component of giving behavior, a recent meta-analysis by Chapman et al. [6] showed that even though trust is often assumed to affect giving, the body of evidence available for their analysis was rather small. Against this background, a first research idea relates to investigations of public trust among different nonprofit organizations based on, for example, the ICNPO categories, organizational mission categories, or other classifications. Precisely, public trust may be high relating to cultural organizations, but lower in the health sector, and thus vary among the different organizations. Evidence also confirms the link between people's trust and the organizations' mission category. Considering the organizational diversity in the nonprofit sector, scholars, such as Kearns [1] and O'Neill [56], propose a more differentiated perspective to distinguish between several nonprofit industries. Further research should take the organizational diversity in the nonprofit sector into account.

Second, few operationalizations and measurement approaches focus explicitly on the public's trust in nonprofit organizations. Given the high importance of the public's trust for nonprofits and corresponding ways to measure it, the second future research idea relates to scale development processes for public trust. These processes should accordingly be based on the broader trust perspective, such that they relate to weaker relationships between organizations and the general public. On the one hand, scholars could build on Sargeant and Woodliffe's [41] measurement scale, and include additional items that address the five trust driving mechanisms. On the other hand, scholars could operationalize public trust as a secondorder construct. The five mechanisms accordingly provide the basis for first-order dimensions, and corresponding measurement items respectively.

Third, nonprofit branding and nonprofit accountability strategies are first attempts to improve and restore public's trust in nonprofit organizations. However, conceptual and empirical research on the link between public trust and accordant research fields and strategies still is limited. Yet, both nonprofit branding and nonprofit accountability have gained increasing importance over the past few years, and scholars have found them to be very promising, in particular in the context of trust research [8, 10, 32, 48, 49]. Another future research idea accordingly refers to this topic, to further investigate the link between these research fields and public's trust. Findings could be used to provide nonprofit managers with more specific recommendations to further improve public's trust in nonprofit organizations. This chapter thus points to the overall need to further the public trust discussion.

*The Psychology of Trust*

### **Author details**

Annika Becker

Lucerne University of Applied Sciences and Arts, School of Business, Institute of Management and Economics, Competence Center Public and Nonprofit Management, Lucerne, Switzerland

\*Address all correspondence to: annika.becker@hslu.ch

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Trust in the Nonprofit Domain: Towards an Understanding of Public's Trust… DOI: http://dx.doi.org/10.5772/intechopen.100636*

### **References**

[1] Kearns KP. 2014. Ethical challenges in nonprofit organizations: Maintaining public trust. In: Frederickson HG, Ghere RK, editors. *Ethics in Public Management*. London/New York: Routledge; 265-292

[2] Bryce HJ. 2007. The public's trust in nonprofit organizations: The role of relationship marketing and management. California Management Review **49**(4): 112-131

[3] Burt CD. 2014. *Managing the Public's Trust in Non-Profit Organizations*. New York, NY: Springer

[4] Ortmann A, Schlesinger M. 2003. Trust, repute, and the role of nonprofit enterprise. In: Anheier HK, Ben-Ner A, editors. *The Study of the Nonprofit Enterprise*. New York, NY: US Springer. pp. 77-114

[5] Rose-Ackerman S. 1996. Altruism, nonprofits, and economic theory. Journal of Economic Literature. **34**(2): 701-728

[6] Chapman CM, Hornsey MJ, Gillespie N. 2021. To what extent is trust a prerequisite for charitable giving? A systematic review and meta-analysis. *Nonprofit and Voluntary Sector Quarterly*. DOI:08997640211003250

[7] Sargeant A, Lee S. 2002. Improving public trust in the voluntary sector: An empirical analysis. International Journal of Nonprofit and Voluntary Sector Marketing. **7**(1):68-83

[8] Sargeant A. 2009. *Marketing Management for Nonprofit Organizations*. 3rd ed. Oxford University Press: Oxford

[9] Hansmann H. 1980. The role of nonprofit enterprise. The Yale Law Journal. **89**(5):835-902

[10] Prakash A, Gugerty MK. 2010. Trust but verify? Voluntary regulation programs in the nonprofit sector. Regulation & Governance. **4**(1):22-47

[11] Brady MK, Bourdeau BL, Heskel J. 2005. The importance of brand cues in intangible service industries: An application to investment services. Journal of Services Marketing. **19**(6): 401-410

[12] Venable BT, Rose GM, Bush VD, Gilbert FW. 2005. The role of brand personality in charitable giving: An assessment and validation. Journal of the Academy of Marketing. **33**(3): 295-312

[13] Tremblay-Boire J, Prakash A, Gugerty MK. 2016. Regulation by reputation: Monitoring and sanctioning in nonprofit accountability clubs. Public Administration Review. 76(5): 712-722

[14] Willems J, Jegers M, Faulk L. 2016. Organizational effectiveness reputation in the nonprofit sector. Public Performance and Management Review. **39**(2):476-497

[15] Becker A, Boenigk S, Willems J. 2020. In nonprofits we trust? A largescale study on the public's trust in nonprofit organizations. Journal of Nonprofit & Public Sector Marketing. **32**(2):189-216

[16] Bourassa MA, Stang AC. 2016. Knowledge is power: Why public knowledge matters to charities. International Journal of Nonprofit and Voluntary Sector Marketing. **21**(1): 13-30

[17] Naskrent J, Siebelt P. 2011. The influence of commitment, trust, satisfaction, and involvement on donor retention. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations. **22**(4):757-778

[18] Edmondson AC. 2004. Psychological safety, trust and learning: A group-level lens. In: Kramer R, Cook K, editors. *Trust and Distrust in Organizations: Dilemmas and Approaches*. New York: Russell Sage; pp. 239-272

[19] Morgan RM, Hunt SD. 1994. The commitment–trust theory of relationship marketing. Journal of Marketing. **58**(3):20-38

[20] Feldheim MA, Wang X. 2004. Ethics and public trust: Results from a national survey. Public Integrity. **6**(1): 63-75

[21] McDonald RE. 2007. An investigation of innovation in nonprofit organizations: The role of organizational mission. Nonprofit and Voluntary Sector Quarterly. **36**(2):256-281

[22] Wiepking P, Bekkers R. 2012. Who gives? A literature review of predictors of charitable giving. Part Two: Gender, family composition and income. Voluntary Sector Review. **3**(2):217-245

[23] Helmig B, Hinz V, Ingerfurth S. 2015. Valuing organizational values: Assessing the uniqueness of nonprofit values. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations. **26**(6):2554-2580

[24] Aaker J, Vohs KD, Mogilner C. 2010. Nonprofits are seen as warm and for-profits as competent: Firm stereotypes matter. Journal of Consumer Research. **37**(2):224-237

[25] Frumkin P. 2009. *On Being Nonprofit: A Conceptual and Policy Primer*. Cambridge, MA: Harvard University Press

[26] Oxfam. 2021 (ed.). *What we believe*. Retrieved from: https://www.oxfam.org/ en/what-we-do/about/what-we-believe.

[27] Rainey HG, Steinbauer P. 1999. Galloping elephants: Developing

elements of a theory of effective government organizations. Journal of Public Administration Research and Theory. **9**(1):1-32

[28] Lange D, Lee PM, Dai Y. 2011. Organizational reputation: A review. Journal of Management. **37**(1):153-184

[29] Sarstedt M, Schloderer MP. 2010. Developing a measurement approach for reputation of non-profit organizations. International Journal of Nonprofit and Voluntary Sector Marketing. **15**(3):276-299

[30] Shahid S, Becker A, Kundi YM. 2021. Do reputational signals matter for nonprofit organizations? *Management Decision*: An experimental study; DOI: 10.1108/MD-12-2020-1670

[31] Ali R, Jin Z, Wu K, Melewar TC. 2016. How does reputation win trust? A customer-based mediation analysis. *International Studies of Management and Organization* **47**(3): 220-239

[32] Becker A. 2018. An experimental study of voluntary nonprofit accountability and effects on public trust, reputation, perceived quality, and donation behavior. Nonprofit and Voluntary Sector Quarterly. **47**(3): 562-582

[33] Greiling D. 2007. Trust and performance management in non-profit organizations. The Innovation Journal: Public Sector Innovation Journal. **12**(3): 9-32

[34] Schnackenberg AK, Tomlinson EC. 2014. Organizational transparency: A new perspective on managing trust in organization-stakeholder relationships. *Journal of Management*. 42(7):1784-1810

[35] Gugerty MK. 2009. Signaling virtue: Voluntary accountability programs among nonprofit organizations. Policy Sciences. **42**(3):243-273

*Trust in the Nonprofit Domain: Towards an Understanding of Public's Trust… DOI: http://dx.doi.org/10.5772/intechopen.100636*

[36] Arvidson M, Lyon F. 2014. Social impact measurement and non-profit organisations: Compliance, resistance, and promotion. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations. **25**(4):869-886

[37] Bekkers R. 2003. Trust, accreditation, and philanthropy in the Netherlands. Nonprofit and Voluntary Sector Quarterly. **32**(4):596-615

[38] Schiessl M. 2014. Financial scandal: Organizational change has led to chaos in Greenpeace. http://www.spiegel.de/ international/business/greenpeace-fina ncial-scandal-how-the-organiza tion-lost-millions-a-976868.html [24 May 2016].

[39] charity: water. 2021 (ed.). *The 100% Model*. Retrieved from https://www.cha ritywater.org/our-approach/100-perce nt-model.

[40] Nunnally JC, Bernstein IH. 1994. *Psychometric Theory*. 3rd ed. McGrawHill: New York, NY

[41] Sargeant A, Woodliffe L. 2007. Building donor loyalty: The antecedents and role of commitment in the context of charity giving. Journal of Nonprofit & Public Sector Marketing. **18**(2):47-68

[42] Sargeant A, Ford JB, West DC. 2006. Perceptual determinants of nonprofit giving behavior. Journal of Business Research 59(2): 155-165

[43] Fornell C, Larcker DF. 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research. **18**(1):39-50

[44] Bies A. 2010. Evolution of nonprofit self-regulation in Europe. Nonprofit and Voluntary Sector Quarterly. **39**(6): 1057-1086

[45] Sargeant A, Lee S. 2004. Trust and relationship commitment in the United Kingdom voluntary sector: Determinants of donor behavior. Psychology & Marketing. **21**(8):613-635

[46] Sargeant A, Lee S. 2004b. Donor trust and relationship commitment in the U.K. charity sector: The impact on behavior. Nonprofit and Voluntary Sector Quarterly. **33**(2):185-202

[47] MacMillan K, Money K, Money A, Downing S. 2005. Relationship marketing in the not-for-profit sector: an extension and application of the commitment–trust theory. Journal of Business Research. **58**(6): 806-818

[48] Slatten LAD, Guidry BN, Austin W. 2011. Accreditation and certification in the non-profit sector: Organizational and economic implications. Organization Management Journal. **8**(2):112-127

[49] Laidler-Kylander N, Stenzel JS. 2013. *The Brand IDEA: Managing Nonprofit Brands with Integrity, Democracy, and Affinity*. San Francisco: John Wiley

[50] Sargeant A, Ford JB, Hudson J. 2008. Charity brand personality: The relationship with giving behavior. Nonprofit and Voluntary Sector Quarterly. **37**(3):468-491

[51] Boenigk S, Becker A. 2016. Toward the importance of nonprofit brand equity: Results from a study of German nonprofit organizations. Nonprofit Management and Leadership. **27**(2): 181-198

[52] Kylander N, Stone C. 2012. The role of brand in the nonprofit sector. Stanford Social Innovation Review 10 (2): 35-41

[53] Chun Feng N, Gordon Neely D, Slatten LA. 2015. Accountability standards for nonprofit organizations: Do organizations benefit from

certification programs? International Journal of Public Administration; **39**(6): 470-479

[54] Herzlinger RE. 1996. Can public trust in nonprofits and governments be restored? Harvard Business Review. **74**(2):97-107

[55] Light PC. 2008. *How Americans View Charities: A Report on Charitable Confidence*. Washington, DC: Brookings Institution

[56] O'Neill M. 2009. Public confidence in charitable nonprofits. Nonprofit and Voluntary Sector Quarterly. **38**(2): 237-269

### **Chapter 12**

## A Coke by Any Other Name: What New Coke Can Teach about Having Trust, Losing Trust, and Gaining It Back Again

*Martha Peaslee Levine and David M. Levine*

### **Abstract**

For 99 years, Coca-Cola sold itself as an American icon made with a secret recipe that was locked away in an Atlanta vault. Then, in 1985, in an attempt to compete with Pepsi-Cola, Coca-Cola changed the taste of Coke. After an uproar, the old version of Coke was reissued as Coke Classic; New Coke faded away. Evidence shows that New Coke tasted better, so it should have been eagerly accepted by the public. But it was not. Why did changing a long-term brand to a better-tasting alternative fail? Examining this issue from both the psychological and legal dimensions, we come to understand many aspects of this failed experiment, which can be useful for other brands interested in making transitions. It is clear that if companies use psychological tools to connect consumers to a brand and trademark law tools to strengthen and protect that connection, they risk adverse reactions and criticism if they then change the brand. Tools that can guard a brand from competitors can also lock it into a cage with tightly defined expectations by the public. Because advertising through media and sports generates strong connections with these beverages, health concerns and possible future research on obesogenic behaviors are considered.

**Keywords:** trademark, brand name, psychology of trust, Coca-Cola, icon

### **1. Introduction**

There is significant research about brands and how to create customer loyalty. When creating an authentic brand, companies need to consider continuity, integrity, originality, and credibility [1]. These dimensions are all equally important and can suggest why Coca-Cola ran into difficulties when it introduced New Coke. Coca-Cola had been using the same original formula for 99 years. That continuity connected consumers with its brand and ensured those consumers knew what to expect every time they cracked open a bottle or can of Coke. It was made from a closely guarded secret formula. Throughout those 99 years, Coca-Cola acted with credibility and integrity. It gave consumers what they had come to expect in taste at a fair and reasonable price. Consumers remained loyal to the brand and expected the brand to remain loyal to them. They expected Coca-Cola to continue to provide the original and unique taste that they had come to anticipate.

In 1985 a new formula of Coke was introduced. Coca-Cola's brand was being edged out of the market by Pepsi-Cola, which offered a sweeter cola taste. Pepsi-Cola advertised that it beat Coke in blind taste tests [2]. Coca-Cola adjusted its formula to meet this challenge. In blind taste tests, New Coke won over the old Coke version. It also beat Pepsi-Cola. Coca-Cola saw this as a way to take over an even larger share of the market. Yet, all that Coca-Cola received from this effort was significant criticism and controversy. Consumer outcry was so significant that after only 77 days, Coca-Cola had to reissue the original formula as Coca-Cola Classic [3]. This chapter reviews emotional and legal issues related to branding and the psychology of trust to help advance our understanding of what occurred within this failed experiment. Other brands or individuals can use this information to understand the psychology of trust as it relates to products—especially those that during their long history have taken on the status of an icon.

### **2. Methods**

The literature was examined related to the psychology of trust and brands. First, historical data was reviewed to understand the timeline of the Coke/New Coke transition. Without understanding the history of the Coca-Cola brand, it is impossible to understand what occurred when they changed their formula. The authors then reviewed psychological and legal references to examine facets of this case. Psychological and legal arguments help us understand what Coca-Cola did not completely consider and why their new taste experiment failed. The literature also helps us understand how Coca-Cola was able to win back the public's trust. Additionally, from the literature, the authors identify potential future health challenges related to branding and the complicated interaction between individuals and products.

### **3. History**

In Ref. [4], the authors describe how the situation with New Coke occurred. "In the late 1970s and early 1980s, Coca-Cola's market share was falling while Pepsi's was on the rise. These trends were contemporaneous to PepsiCo's 'Pepsi Challenge' national marketing campaign of public blind taste tests…. Even worse, the Coca-Cola Company conducted its own blind taste tests and found that, indeed, consumers preferred Pepsi by margins as high as 10–15 points." [4, p. 1037] Even though the taste tests said that Pepsi was the winner, Coke was still holding strong. However, Coca-Cola worried about losing its market share.

The Coca-Cola Company spent over 2 years and 4 million dollars to develop an improved formula that beat Pepsi in blind taste tests [5]. "The new formula contained less phosphoric acid to give the drink less bite and a smoother taste. In addition, to replace the acidity lost by reducing the phosphoric acid, more citric acid was added; this provided more of a lemon aroma. The new formula also had more fructose and was therefore sweeter." [4, p. 1038].

What did this new formula mean? It meant that in blind taste tests, this new taste of Coke outperformed that of Pepsi and the original Coke. As Levy and Young [4, p. 1038] describe, "The efforts appeared to have paid off: after an exhaustive battery of 190,000 blind taste tests, the new formula was beating Pepsi by a margin of 6–8 points. (It was also beating the original Coca-Cola in these taste tests.) New Coke was introduced with a huge fanfare in New York City on April 23, 1985. It was made clear to consumers that the drink had undergone a substantial quality change." [4, p. 1038].

*A Coke by Any Other Name: What New Coke Can Teach about Having Trust, Losing Trust… DOI: http://dx.doi.org/10.5772/intechopen.108982*

The public was not impressed.

The Coca-Cola Company even tried to entice consumers with a new ad campaign, using Bill Cosby, who at that time was seen as an attractive, humorous, appealing character. He tried to push the belief that "new is good." [6] The only individuals who were persuaded that New Coke was good were those who initially had negative or neutral attitudes toward Coke. In taste tests, they liked New Coke. However, individuals who usually drank Coke and held positive feelings toward this product now felt betrayed and rejected New Coke [6].

What was Coca-Cola's response? They brought back the old formula of Coke rather than risking the loss of even more of the market share. "Less than 3 months and more than 40,000 letters and 400,000 phone calls from angry consumers later, Coca-Cola Classic (the original "Secret Formula") was brought back, while New Coke was gradually pulled off the market." [4, p. 1032].

This chapter will consider factors in this failed attempt to change a product.

### **4. Emotional connection**

It is clear that consumers had an emotional connection to Coke. Consumers react to products, such as Coke, in more ways than can be measured by a taste test. Individuals could remember when they had their first Coke. In Ref. [7], the authors worked with individuals to understand memories related to Coke and learned about the many connections that individuals had to Coke. Many had memories of sharing a Coke as a bonding experience with a parent or an older family member. Others spoke of receiving a Coke as a reward for good behavior or grades. "In these special parental bonding experiences, the underlying emotion is love and a feeling of belonging or acceptance." [7, p. 331] A depth of feeling became connected with Coke.

All brands want to create memorable experiences. Coke did that by creating a wealth of connections between individuals. Even simple moments were imbued with such a rich emotional experience that they took on more than the causal sharing of a drink. It became a "sacred totem." In Ref. [7], we understand the many mythic images that Coke took on for individuals. It was the transformer—a Coke shared as someone came of age, the hero—always there to give a special boost to parties, and the mother/caretaker—shared at a grandmother's house, a safe and secure place. It is as if these early emotional experiences were "imprinted" and led to a preference for that beverage later in life. When we connect memories of Coke to the mythic structure, we recognize that Coke moved from being a simple beverage to being a placeholder for many emotions. And like the trauma of losing a treasured teddy bear or blankie, the change to New Coke rocked people emotionally. This is why the reaction against New Coke was so strong.

Even neurobiology demonstrates the emotional connection to Coca-Cola. A study [8] demonstrated that the ventromedial prefrontal cortex (VMPC), which is involved in emotions, affected individuals' connections to specific brands. They completed a blind taste test with three categories of subjects: (1) normal controls, (2) individuals who had brain damage in their VMPC, and (3) individuals who had experienced brain damage but which did not affect the VMPC area. In blind taste tests between Coke and Pepsi, all of the individuals preferred Pepsi. (This replicates some of the famous taste challenges that prompted Coke to try and redesign its formula.) However, in taste tests that included brand information, only the individuals with damage to the VMPC area kept their Pepsi preference. When brand information was provided, the other two groups switched their preference from Pepsi to Coke. It was believed that since the VMPC is important in emotional processing,

and brands ensure brand loyalty through emotional connections, the individuals with VMPC damage lost that emotional connection to the brand and only the taste itself determined their preference. Another study found more activation in the right amygdala with a Coca-Cola cue versus Pepsi-Cola; again, this is part of the brain that is associated with emotional processing [9]. In their taste test, they used the exact same mixture of colas for every tasting but found a higher rating of pleasantness and a preference for the drink when the taster believed it to be Coca-Cola or Pepsi-Cola (strong brands) when compared with "weaker" or less-well-known brands. One's emotional connection to a brand affects an individual's perception of a product.

Individuals connected Coke with certain experiences and emotions. When the taste of Coke was not only changed but the change was advertised and presented as a good thing, those memories were affected. Customers are not just consumers but "complex and multi-dimensional human beings." [10, p. 1] Products are not just a thing; they create emotional connections. Coca-Cola promised and delivered on many emotional experiences related to its product. It was precisely because of these connections that its customers felt so violated by the change to New Coke. Consider that when a branded product has been around a long time and is heavily advertised, it can pick up emotional freight [11]. With all of that emotional freight, is it any wonder that the change to New Coke derailed?

### **5. Coke as an icon and resistance to change**

Coca-Cola wove itself into the American fabric. When Coke changed, individuals went to great lengths to hold on to their icon. Some stories included grandparents who stocked cases of Old Coke or news announcements on the radio in Georgia announcing what locations still had Old Coke and any restrictions on the amount people could buy [7]. One can hear in these memories the uproar that the change in Coke had on families. That was especially true in the South and even more so in Atlanta, Georgia, home of Coca-Cola headquarters. It prompted individuals to hoard old Coke or go in search of the remaining cases. There are many potential reasons for this almost fanatical devotion to Coke. It could be the fact that Coca-Cola was made in the South, it could be the memories associated with this drink that caused such angst, or it could be the fact that traits associated with a conservative ideology, measured by voting behavior and religiosity, are linked with a preference for established national brands. Individuals with conservative leanings have a lower tendency to buy newly launched products. These individuals prefer tradition and the status quo. They avoid uncertainty and are skeptical about new experiences [12]. Coca-Cola did not factor those tendencies into its decision to make the change from its tried-and-true formula to something new.

Reference [13] considers that there are two types of brands—sincere and exciting. Coca-Cola was and is within the sincere grouping—it is stable and reliable. The exciting brand category includes Mountain Dew, which tries to inspire the rebel spirit. Sincere brands often have stronger relationships with their customer base, which is part of the reason that New Coke stumbled. The consumers placed the original Coca-Cola on a pedestal. It was as American as the Constitution. However, because of this strong and trusting relationship, sincere brands can run into more difficulties than exciting brands if a transgression occurs. In Ref. [13], they found that transgressions (substantial changes) weakened the relationship with a sincere brand. However, the exciting brand not only wasn't as affected by a change but was also at times reinvigorated. It seems that with the exciting brand, consumers are willing to be more flexible. They are willing to expect the unexpected [13].

*A Coke by Any Other Name: What New Coke Can Teach about Having Trust, Losing Trust… DOI: http://dx.doi.org/10.5772/intechopen.108982*

Coca-Cola was able to recover from its transgression. Perhaps it was because they acknowledged their mistake and quickly brought back the requested original formula. They had believed from their taste test research that they knew what consumers wanted. When it was clear that they had misinterpreted the evidence, instead of trying to convince the consumer that the new Coke was better, they brought back the original, which had become an icon and was a sincere and stable brand

### **6. Trust and brand**

"The brand name is the customer's guarantee that he will get what he expects." [11] That is where trademark law comes in. As Bone [14, p. 549] notes, one of the foremost goals of trademark law is "information transmission." Trademarks are used "as devices for communicating information to the market" and trademark law works to "prevent others from using similar marks to deceive or confuse consumers." In this conception, trademarks and trademark law serve to both guide and protect consumers [14, pp. 555–56]. Trademarks are guideposts, landmarks that a consumer can look to and rely on when making a purchase. Trademark law is a shield against attempts to deceive consumers into purchasing products based on a false belief that it is the brand they desire. Trademarks also aid consumers by providing incentives to businesses to produce high-quality products, which consumers will know to return to and purchase again because of the reliable association with that business's trademark. The Supreme Court succinctly summarized this overarching goal when it noted that a trademark "helps consumers identify goods and services that they wish to purchase, as well as those they want to avoid." [15, p. 1751] Trademark law helps prevent knockoffs that will affect the trust that they (the brands) have worked to establish with the consumer.

Sahin, Zehir, and Kitapçı [16, p. 1297] describe that "brand experience has positive effects on brand satisfaction, trust and loyalty." Brand experience creates the consumer's trust with the brand and leads to their loyalty. This idea, too, is accounted for in trademark law through the concept of "goodwill." Scholars such as Robert Bone have identified tension between the traditional information transmission theory of trademark and the ways in which trademark law has expanded to protect trademarks that are not necessarily required for them to serve their signaling purpose to consumers [14]. In other words, companies defend their trademarks not just to protect against encroachment on their brand by a similar but lesser quality alternative but also to defend the trademark or name of the company itself. This is to ensure that other products cannot weaken the trademark or the emotional connection that consumers have with these brands.

These expansions are a company's efforts to protect "the special value that attaches to a mark when the seller's advertising and investments in quality generate consumer loyalty." [14, p. 549] Companies, recognizing the value that exists in the trust and the goodwill they have built with consumers, zealously protect their trademarks against misappropriation in all circumstances. As Bone notes, "It does not matter whether consumers are confused or even whether the defendant's use diverts business from the plaintiff." [14, p. 550]. As the Supreme Court noted, trademark law often intervenes simply when a malfeasor attempts to "reap where it has not sown." [17] As brands and their associated marks become more saturated with goodwill, and thus more and more valuable, these efforts can skyrocket. One need only look to Apple Computer's challenges to marks ranging from the logo of the school district in Appleton, Wisconsin, to an exploding pineapple grenade logo to see the lengths valuable brands will go to protect their name and goodwill [18]. Even though these products would not be confused with Apple, it defends against

these efforts because it wants to ensure that no one can encroach on its name. It is like a slippery slope. A company defends against any potential encroachment so that another brand cannot gain a foothold and rely on the goodwill that the original company has created with consumers.

While goodwill-based explanations about trademark law are often focused on companies' efforts to protect marks (and associated goodwill) that they view as property, the relationship between trust and brands provides a more publicand consumer-focused rationale. We have seen how individuals' experiences with Coke led to trust in the brand. Trademarks played an important part in this trust-building process. Coke spent decades building consumer trust in its iconic trademarks so that consumers knew what exactly to expect from a bottle (often glass and shaped with iconic contoured lines) that was emblazoned with a recognizable, flowing script spelling a ubiquitous name: Coca-Cola. Trademark law protects these vessels of trust and goodwill from those who would misappropriate them.

But even trademark law cannot protect a company from itself. When Coke was changed, that trust was violated. Reference [16] describes that satisfaction with a brand is part of what determines brand loyalty. When Coca-Cola changed from its classic formula to New Coke, customers were not satisfied. They had pledged their loyalty to Coke and had come to trust and expect a certain taste from Coke. When that was suddenly and unexpectedly changed, consumers felt that Coke had let them down. In many ways, the depth of the reaction was because Coke was felt to be such a part of the American culture [7]. Coca-Cola connected with the American dream through many avenues, including sports, and used these events as an "advertising arena" [19]. Later, they went on to try and conquer the world through the 1970s ad campaign that focused on teaching "the world to sing in perfect harmony." [19] When a company works so hard to build a brand and seep it into a country's culture, it should expect pushback when it then changes that brand.

This emotional attachment, this built-up trust, not just in a brand itself but also in a particular form of a brand, casts complexity into the basic framework of our understanding of trademarks. One could view the standard information transmission model as somewhat paternalistic—trust us, the brand says, because we always deliver quality and will continue to deliver quality (even if that quality comes in a somewhat different form). As long as the consumer knows, trusts, and can seek out a brand, those goals of trademark law are satisfied. The uproar around New Coke casts doubt on this simplistic view. Consumers trusted Coke not just because it was Coke but also because of the core memories and specific attachments they had formed around Coke as it was. As Desai [20, p. 985] notes, "Consumers often buy branded goods not for their quality but as badges of loyalty, ways to express identity, and items to alter and interpret for self-expression." A brand, and the trademarks that often sit at the heart of that brand, do more than the mechanical task of directing customers to good companies and products and away from bad ones. Instead, brands and the specific products they embody often become organically entwined in the hearts and minds of consumers and our culture as a whole.

Later, long after the New Coke debacle, Coke seemed to recognize this fact and became attuned to the attachment consumers had to both the brand and the taste of Coke. A 2007 humorous ad campaign focused on the idea of "taste infringement" to highlight the similarity between Coke Zero and Coca-Cola [21]. Now, instead of wanting to change the flavor of Coke, the company wanted to link a new product to the iconic original.

*A Coke by Any Other Name: What New Coke Can Teach about Having Trust, Losing Trust… DOI: http://dx.doi.org/10.5772/intechopen.108982*

### **7. Implicit contract**

Reference [4] discusses how Coca-Cola had entered into an implied contract with the American public over the 99 years that it produced its drink using its secret formula. "An implicit contract is an unwritten, legally non-binding understanding that all parties have incentives to preserve." [4, p. 1033] Coke had used its brand and trademark to lead to consumer expectation. It felt like an implied contract—you are buying Coke and will get the same product that we have provided for the last 99 years. When Coca-Cola completely changed its formula and taste, it broke its side of the deal. The consumers had the option of walking away from the product (and many did boycott Coca-Cola) or voicing their displeasure. Loyal customers did not feel like they had other good cola options; they did not want to exit. They wanted their original Coke back. And so they voiced their opinions!

Here are some examples from reference [22, pp. 335–336]:

*My littele sisther is cring because coke changed and she sayed that shed is not going to stop cring every day until you chang back…. I am getting tryer of hearing her now if you do not chang I'll sue evne if I'm just 11.*

*Changing Coke is like breaking the American dream, like not selling hot dogs at a ball game.*

*For years, I have been what every company strives for: a brand-loyal consumer. I have purchased at least two cartons of Coke a week for as long as I can remember…. My "reward" for this loyalty is having the rug pulled out from under me. New Coke is absolutely AWFUL…. Do not send me any coupons or any other inducement. You guys really blew it.*

*Millions of dollars worth of advertising cannot overcome years of conditioning. Or in my case, generations. The old Coke is in the blood. Until you bring the old Coke back, I'm going to drink RC.*

*Would it be right to rewrite the Constitution? The Bible? To me, changing the Coke formula is of such a serious nature.*

As Levy and Young [4, p. 1047] describe, "The Coca-Cola Company assumed that its brand equity would transfer to New Coke; instead, the replacement of the original Coca-Cola was harmful to that equity." The authors go on to say [4, p. 1047], "This was true because that brand equity was based, in large part, on an implicit promise of constant quality; and after nearly a century, that promise was reneged on." The key word here is "*constant* quality." For 99 years, Coke had offered an original and authentic product, gained loyalty, and then suddenly announced that the original product was gone and being replaced by New Coke, which was supposed to taste better. That is what the taste tests showed.

This can become complicated. Certainly, there are times that products can be upgraded and improved and the consumers are happy for the change instead of fighting against it. This case allows us to consider the other side of innovation. Taste is, after all, subjective and thus features an emotional component. Even if a certain taste is "better" objectively in tests, the lack of that emotional resonance can make it subjectively worse. If the culture aligns itself with the product, there will be the expectation by many that it should remain stable. Also, as we will see below, there was an element of the consumer immediately losing the old product, which

triggered a psychological reaction. The taking away of something can feel like an assault especially when significant emotions are connected to that product.

### **8. Recovering from the error**

In many ways, Coca-Cola was fortunate. As LaTour, LaTour, and Zinkhan [7, p. 329] describe, "The success of Coca-Cola following the New Coke debacle may be due in part to the brand's personality as well as fitting a defined myth (American dream). The brand was able to recover so quickly because the market 'knew' the brand to be sincere and when the company apologized for their 'marketing mistake' consumers not only forgave them, but came back to them with reinvigorated passion." In many ways, they wanted to return to the myth. They had used their American gumption and brought an American company back to heel. Once they got their original Coca-Cola back, they were willing to look past that transgression. It has been pointed out that although Coca-Cola lost the millions of dollars that it invested in research, through the whole debacle, it may have gained three times as much in free advertising [3].

Coke had tried to do its homework before introducing New Coke. One thing that they forgot is that the lab is not life. In blind taste tests, New Coke outperformed Pepsi and Old Coke [2]. Reference [23] reminds us that in the past, Coke had changed its formula without fanfare or pushback. In the 1960s, Coke slowly and subtly reduced its caffeine content to 1/3 its previous level. At additional times, minor changes were made either because they were legally mandated or to maintain quality. In 1942 a small amount of saccharine was added and the amount of caffeine and coca leaves decreased because of WWII and rationing [4]. However, none of those changes were major or were announced to the public.

Could Coke have gradually changed the taste such that the consumer did not notice and eventually have gotten from Old Coke to New Coke? In [23], the authors discuss this prospect and suggest that it could have been accomplished. Part of the issue for Coca-Cola was that they changed Coke's taste drastically, announced the change so that individuals had an emotional reaction, and took away Old Coke. Undoubtedly, Coke officials were worried that if they started tampering with the Coke formula and that came to light, it could also destroy the trust in Coke completely.

It wasn't just taste that was the issue. The Coke experience held emotion and myth. Coca-Cola did not consider "how groupthink could poison individuals into thinking that the new product was actually inferior, and that taking away the old formula was a mistake." [5, p. 3] Even though the taste tests suggested that New Coke was superior, once negative emotion got stirred up and related to New Coke, it was seen as inferior. Newspapers and radio stations bemoaned the fact that old Coke had been replaced.

It does seem that one of the main reasons for the consumer discontent was that old Coke was *replaced* by New Coke. If New Coke had been introduced alongside and not instead of old Coke, consumers might not have had such a strong reaction [5]. This was demonstrated with later introductions of flavors and with the addition of Diet Coke and then Coke Zero. Diet Coke was not eliminated when Coke Zero was introduced. Psychologists and Ringold [24] define a reactance effect—that when something is taken away, it leads to a potential negative response for a few reasons. One, individuals do not like to be restricted. Replacing something that you are using with something else is essentially taking away the individual's choice. In addition, once something is gone, there is a yearning for what cannot be had. This increases the negative response. These emotional responses can lead to aggression

*A Coke by Any Other Name: What New Coke Can Teach about Having Trust, Losing Trust… DOI: http://dx.doi.org/10.5772/intechopen.108982*

against the perpetrator in an attempt to restore the previous freedom. We have discussed that consumers did turn their aggression against the Coca-Cola Company when the New Coke phenomenon occurred.

### **9. Possible future research: Branding concerns as related to negative health effects**

This chapter shows the power of brands and the dangers to companies when they break from the brand that they created. Brands can become emotionally intertwined with our lives, our self-perception, and our daily behaviors. Brands can connect with public consciousness and our individual sense of self. Companies welcome that attachment to their brand. It ensures loyalty.

As individuals, clinicians, and consumers, we must recognize the other side of the coin. In the end, the public influenced Coke's behavior. Yet there are many more times that soft drink and snack food companies influence consumers' behaviors. We see the potential risks of branding and loyalty as societies battle the negative health risks of obesity.

In particular, there are concerns about how branding (where and how it is presented) might impact individuals, especially children and teens. In Ref. [25], the authors considered recent PR campaigns of Coca-Cola, which were designed to target teenagers and their mothers. These campaigns are a significant concern from the public health arena because of rising obesity rates. Authors in Ref. [26] found that a child's ability to recognize food brands predicted health outcomes such as a preference for foods that are obesogenic and lead to children being at an increased risk to be overweight. In particular, children who watch more TV advertisements develop a more positive association to certain food and drink brands. This attachment was not seen for children who did not watch the commercials—either watched broadcasts with no advertisements or skipped through the commercials [27]. Clearly, there is a concern. As children and adolescents are exposed to unhealthy products and develop a connection to these brands, they start to desire them and demand them. This can start unhealthy food-and-drink patterns from an early age.

When non-nutritious foods are targeted to adolescents, they develop a desire for these substances, and that can fuel soda consumption and weight gain and affect health. Studies have looked at the prevalence of food-and-drink marketing on livestreaming platforms and have raised concerns about the potentially negative effect on overall health. Energy drinks dominate the brands mentioned, but soda and snacks are also prevalent. There was also a huge growth in the use of these platforms during the Covid-19 pandemic, thereby targeting more consumers, many who are young adults [28]. YouTube video bloggers (influencers) who are popular with children often present unhealthy foods in a positive way by describing them more positively as compared to healthy foods, inserting specific brands into their videos, and being engaged in marketing campaigns [29]. Other influencers, music celebrities who are popular with adolescents, often endorse energy-dense, nutrientpoor products, with specifically full-calorie soft drinks being highly endorsed [30]. A study in Australia looked at Facebook and found that energy-dense, nutrientpoor foods, including high-calorie soft drinks, were frequently marketed and integrated seamlessly with online social networks [31]. The authors found that adolescents and young adults engaged with these products almost daily and willingly shared the messages, which continued to spread this relationship to non-nutritious foods and drinks [31]. We see that Coke and other sodas are integrating into these new cultural experiences, connecting with children and teens, and fostering a brand loyalty that can lead to increased soda consumption.

We discussed previously that Coke helped connect itself to the American dream through its selling of the drink in different venues, such as athletic arenas. We see ongoing concerning challenges in this area as well. In Ref. [32], the authors looked at sponsorships of US sports organizations and found that food and beverage were the second largest category of sponsors and the majority of the products in sponsorship commercials were unhealthy. Other studies also demonstrate that sponsorship of sports by brands that sell unhealthy products is common. They advise that this creates an association for fans that links potentially unhealthy products, such as fast food and high-calorie soft drinks, with specific sports, making these products even more appealing [33]. All of these authors express concerns that these brands are being pushed to millions of viewers and urge that marketing pledges should be expanded to limit these potentially negative effects.

Reference [34] looks at the placement of soft drinks in movies and especially the effect of actor endorsement, showing an actor consuming the product. This is a concern because as reference [34] describes, if healthy and physically fit individuals on screen are demonstrated as having a preference for a soft drink and have no negative consequences for repeatedly drinking the soft drink, the message conveyed is that this a normal and healthy behavior. Public health officials worry about these messages especially in light of the obesity challenges that many Americans face. Often these product placements are in children's movies. They are often prominently and positively displayed and are shown as being consumed more often than healthy alternatives. These images are present for all age-rated movies, with no effect of the year (1991–2015) or country of production [35]. As Ref. [36, p. 468] describes, "Movies are a potent source of advertising to children, which has been largely overlooked"

Will this be one of the future challenges of trust in messaging and trust in brands? When loyalty to certain brands occurs because of their connection to movie stars, social media, sports, and other leisure activities, we can see the huge impact that brands and branding can have on the consumer. At times, our trust in brands can lead us astray to nonhealthy behaviors. As we examine the history of Coca-Cola, we see the effect that the public can have on a large corporation. The public brought back the old Coke. Perhaps, public outcry is currently needed to highlight and defeat this current health risk—the subtle marketing of brands that bond children and teens to obesogenic drinks and foods. We know that once someone is firmly connected to a brand, it can, for better or worse, be a significant influence in their life. The way sodas are portrayed in movies, on social media, and through sporting events can clearly foster an unquestioning loyalty that can lead to increased health risks.

### **10. Limitations**

Even though both the psychological and legal literature were used to examine this topic, it is not an exhaustive treatise on the topic of brands as they relate to the psychology of trust. The authors used this one case example to look at many factors that can come into play in the relationship between consumers and brands, especially when brands are changed. The authors also started the conversation of looking at the effect that branding can have on negative health outcomes, such as obesity. This is an area that would benefit from further exploration.

### **11. Conclusion**

Walking down a store aisle, surrounded by product after branded product, it is easy to believe that each brand is simply an attempt by a company to attract your

*A Coke by Any Other Name: What New Coke Can Teach about Having Trust, Losing Trust… DOI: http://dx.doi.org/10.5772/intechopen.108982*

attention and, ultimately, your money. What we know is that brands matter—not just to companies but also to us. A brand like Coca-Cola can work its way into the framework of our lives, into some of our fondest memories. We grow to trust the brand and view it as a friend more than a product or company. That trust has significant implications if a brand tries to change or reshape the terms of that trusting relationship. As New Coke shows, when that trust is broken, it can verge on disaster. With many of the brands that have a constant presence in our life, the attachment is emotional, not logical. That reality has a significant impact on how brands interact with the law, our culture, and ultimately the psychology of how, why, and who we trust.

### **Author details**

Martha Peaslee Levine1 \* and David M. Levine2

1 Penn State College of Medicine, Hershey, PA, USA

2 Washington, DC, USA

\*Address all correspondence to: mpl12@psu.edu

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

### **References**

[1] Portal S, Abratt R, Bendixen M. The role of brand authenticity in developing Brand Trust. Journal of Strategic Marketing. 2019;**27**(8):714-729. DOI: 10.1080/0965254X.2018.1466828

[2] Coke Vs. Pepsi: The Blind Taste Challenge - MARKETING10 [Internet]. 2020. Available from: https://www. marketing10.in/coke-vs-pepsi-theblind-taste-challenge/ [Accessed 22 October 2022]

[3] New Coke | History, Response, & Facts | Britannica [Internet]. others, Kieran Fogarty and. "New Coke". Encyclopedia Britannica. 2018. https:// www.britannica.com/topic/New-Coke [Accessed 24 October 2022]

[4] Levy D, Young AT. Promise, trust, and betrayal: Costs of breaching an implicit contract. Southern Economic Journal. 2021;**87**:1031-1051

[5] Jones K, Ondracek J, Saeed M, Bertsch A. Don't mess with Coca-Cola: Introducing New Coke reveals flaws in decision-making within the Coca-Cola Company. International Journal of Management Research. 2016;**4**(10):2394

[6] Pierce WD. Which Coke is it? Social influence in the marketplace. Psychological Reports. 1987;**60**:279-286

[7] LaTour K, LaTour MS, Zinkhan GM. Coke is it: How stories in childhood memories illuminate an icon. Journal of Business Research. 2010;**63**:328-336

[8] Koengs M, Tranel D. Prefrontal cortex damage abolishes brand-cued changes in Cola preference. SCAN. 2008;**3**:1-6. DOI: 10.1093/scan/nsm032

[9] Kühn S, Gallinat J. Does taste matter? How anticipation of Cola brands influences gustatory processing in the brain. PLoS One. 2013;**8**(4):e61569. DOI: 10.1371/journal.pone.0061569

[10] Gómez-Suárez M, Martínez-Ruiz MP, Martínez-Caraballo N. Consumer-brand relationships under the marketing 3.0 paradigm: A literature review. Frontiers in Psychology. 2017;**8**:252. DOI: 10.3389/ fpsyg.2017.00252

[11] Fisher AB, Steyer R. Coke's Brand-Loyalty Lesson. *FORTUNE Magazine.* 1985 [Internet]. https://archive.fortune. com/magazines/fortune/fortune\_ archive/1985/08/05/66245/index.htm [Accessed 24 October 2022]

[12] Khan R, Misra K, Singh V. Ideology and brand consumption. Psychological Science. 2013;**24**(3):326

[13] Aaker S, Fournier S, Brasel A. When good brands do bad. Journal of Consumer Research. 2004;**31**(1):1-16

[14] Bone R. Hunting goodwill: A history of the concept of goodwill in trademark law. Boston University Law Review. 2006;**86**:547-622

[15] *Matal v. Tam*, 137 S. Ct. 1744. 2017

[16] Sahin A, Zehir C, Kitapçı H. The effects of brand experiences, trust and satisfaction on building brand loyalty; an empirical research on global brands. Procedia Social and Behavioral Sciences. 2011;**24**:1288-1301

[17] International News Service v. Associated Press, 248 U.S. 215, 239 (1918)

[18] Mac R, Browning K. Apps and oranges: Behind Apple's 'bullying' on trademarks. *New York Times*. 2022

[19] Falk P. Coke is it! The Cambridge Journal of Anthropology. 1991;**15**(1):46-55

[20] Desai D. From trademarks to brands. Florida Law Review. 2012;**64**:981-1044

[21] Cox JN. Why Coca-Cola's fictional lawsuit against Coke zero for taste

*A Coke by Any Other Name: What New Coke Can Teach about Having Trust, Losing Trust… DOI: http://dx.doi.org/10.5772/intechopen.108982*

infringement is a losing Battle. Journal of Intellectual Property Law. 2009;**17**(1):121-146

[22] Pendergrast M. For God, Country & Coca-Cola: The Definitive History of the Great American Soft Drink and the Company that Makes It. 3rd ed. New York: Basic Books, Perseus Books Group; 2013. p. 560

[23] Dubow JS, Childs NM. New Coke, mixture perception, and the flavor balance hypothesis. Journal of Business Research. 1998;**43**:147-155

[24] Ringold DJ. Consumer response to product withdrawal: The reformulation of Coca-Cola. Psychology & Marketing. 1988;**5**(3):189-210

[25] Wood B, Ruskin G, Sacks G. Targeting children and their mothers, building allies and marginalising opposition: An analysis of two coca-cola public relations requests for proposals. International Journal of Environmental Research and Public Health. 18 Dec 2019;**17**(1):12. DOI: 10.3390/ijerph17010012. PMID: 31861344; PMCID: PMC6981900

[26] Harrison K, Moorman J, Peralta M, Fayhee K. Food brand recognition and BMI in preschoolers. Appetite. 2017;**114**:329e337

[27] Kelly B, Boyland E, King L, Bauman A, Chapman K, Hughes C. Children's exposure to television food advertising contributes to strong brand attachments. International Journal of Environmental Research and Public Health. 2019;**16**:2358

[28] Edwards CG, Pollack CC, Pritschet SJ, Haushalter K, Long JW, Masterson TD. Prevalence and comparisons of alcohol, candy, energy drink, snack, soda, and restaurant brand and product marketing on twitch, Facebook gaming and YouTube gaming. Public Health Nutrition. 2021;**25**(1):1-12. DOI: 10.1017/ S1368980021004420

[29] Coates AE, Hardman CA, Halford JCG, Christiansen P, Boyland EJ. Food and beverage cues featured in YouTube videos of social media influencers popular with children: An exploratory study. Frontiers in Psychology. 2019;**10**:2142. DOI: 10.3389/ fpsyg.2019.02142

[30] Bragg MA, Miller AN, Elizee J, Dighe S, Elbel BD. Popular music celebrity endorsements in food and nonalcoholic beverage marketing. Pediatrics. 2016;**138**(1):e20153977

[31] Freeman B, Kelly B, Baur L, Chapman K, Chapman S, Gill T, et al. Digital Junk: Food and beverage marketing on Facebook. American Journal of Public Health. 2014;**104**: e56-e64

[32] Bragg MA, Miller AN, Roberto CA, Sam R, Sarda V, Harris JL, et al. Sports sponsorships of food and nonalcoholic beverages. Pediatrics. 2018;**141**(4): e20172822

[33] Ireland R, Chambers S, Bunn C. Exploring the relationship between big food corporations and professional sports clubs: A scoping review. Public Health Nutrition. 2019;**22**(10):1888- 1897. DOI: 10.1017/S1368980019000545

[34] Cassady D, Townsend M, Bell RA, Watnik M. Portrayals of branded soft drinks in popular American movies: A content analysis. International Journal of Behavioral Nutrition and Physical Activity. 2006;**3**:4

[35] Matthes J, Naderer B. Sugary, fatty, and prominent: Food and beverage appearances in children's movies from 1991 to 2015. Pediatric Obesity. 2019;**14**:e12488

[36] Sutherland LA, MacKenzie T, Purvis LA, Dalton M. Prevalence of food and beverage Brands in Movies: 1996-2005. Pediatrics. 2010;**125**(3): 468-474

## *Edited by Martha Peaslee Levine*

Trust has always been complicated. This book works to examine aspects and theories of trust. Chapters look at trust in the workplace. It considers types of leadership and how that influences the trust of employees. As workplaces and societies become more diverse, there can be an impact on trust. Many times, individuals will have implicit biases that can influence their perception of others and their ability to trust. Trust has also become more complicated with the advent of the internet. We can now connect with more ideas and individuals. Yet, is the person who communicates back with us real? Is it someone with a fake account or maybe not even a person at all, but a robot? Even though trust is complicated and we can sometimes be taken advantage of, we still need to find ways to trust others in our lives. Trust allows us to develop a community. We have always needed the community to be safe, both physically and emotionally. This book allows you to connect with new ideas and aspects of trust.

Published in London, UK © 2023 IntechOpen © wildpixel / iStock

The Psychology of Trust

The Psychology of Trust

*Edited by Martha Peaslee Levine*