**1. Introduction**

This text deals with the new discourses of reality in which the main characteristic is the integral, ecological, and holistic vision. It is a worldview where everything is connected to everything. Such is the systemic approach. The idea of a system covers a general type of concepts, conceived by man as complex models of coherence, more or less identifiable and permanent in the real world [1, 2].

Semiotics is the doctrine of all signs, and a sign is something that is in place of something else in any of its properties. This definition creates a path to understanding the randomness of the meaning considering that 'something else' could be referring to anything in terms of technology for memory; for example, the writings and encrypted algorithms have an enormous diversity. Under this view, semiotics integrates Charles Sanders Peirce pragmatism thinking and ideas. From the semiotic framework, a sign is the meeting ground of the relations between elements of two systems, the transmitter, and the receiver, and only can happen in the social community. Each of these elements is entitled to enter—under given coded circumstances—into other correlation and thus form a new sign [3]. Instead, semiosis is a process in which an entity acquires meaning as icon, index, or symbol. Semiosis is a process of structural coupling between the elements of different systems. These systems are (A) a set of possible behavioral responses, (B) a set of states of things in the world, and (C) a set of signals correlated by arbitrary combining.

The term architecture refers to the frame of digital communication. This structure can reach a lot of levels: the defined libraries of algorithms, the processes that they can do, the time of the spread of bits, and the meaning of the data coded on bits. However, the level of our interest is the semiotic one or the meaning coded. We watch a massive response between bits, data, and receivers only on the semiotic level. The theoretical issue of this kind of behavior is the continuous change of the meaning of the information point-to-point until it becomes fake in opposition to reality. The social importance of this behavior is the impact of the offline world. A lot of massive news turns into political and cultural energy: anger, despair, and polarization. Therefore, the control of digital communication is a topic of political power than nations and agents take advantage of them.

It should be noted that, with the development of Web 3.0, the semiotic processes have changed. Digital technologies, in addition to providing interaction and updating in real time, stimulate the development of long-range semantic networks, the interaction of large databases, and increasingly efficient algorithms to navigate [4]. This has caused effects or by-products. Super viral information of networks or cascade is the best example of this kind of outgrowths without control. The cascades are the best example of viral data, and we refer to them in the next pages.

The debate about cascades is if the tendency of information in a network is natural or not. The informal expression of social inclination in digital communication is trending. It refers to a topic currently popular or widely discussed on social media websites; they are today's top trending topics.

Current studies about digital propaganda have proved that some trendings are controlled by human trolls, bots, and algorithms. Most of them have political and hybrid warfare purposes [5–12].

But in this chapter, we will not go deep into political science. Instead, in the theoretical arena of systems research, Prigogine [13] postulated that dissipative systems are dynamic nonequilibrium open systems with internal gradients. They keep their low entropy condition stable by transporting matter and energy beyond their frontiers. They consume energy and present matter and energy cycles. Dissipative structures develop complexity exporting and dissipating entropy to their environment [14–16].

The systems we deal in social sciences, humanities, and arts are open systems. Open systems are those that transform one type of energy, matter, or information into another, as they adapt to their environment. The classic mechanic theory defines that in all open systems, change is irreversible. The shifts within open systems generate all kinds of disturbances at the atomic level, which lead to disorder in the molecular structures until the social macrolevel. These variances into the matter, energy, and information are an irreversible process. This process produces a kind of disorder in the fundamental structure and it is measured by its entropy.

According to Claude Shannon as Ilya Prigogine, entropy or disorder can be characterized as a statistical measure [13, 17]. Shannon's entropy "is a statistical parameter which measures, in a certain sense, how much information is produced on the average for each letter of a text in the language. If the language is translated into binary digits (0 or 1) in the most efficient way, the entropy H is the average number of binary digits required per letter of the original language" [17]. Our writing system has 26 letters to represent many languages. But if I use my alphabetic keyboard to do a translation to a writing system that only has 2 digits, as binary, I have to count how many times the digits of binary systems I need to combine to reach the best codification. The average of binary system required for each letter is 4.6. The formula is very simple: log2 26 = 4.6 bits per letter, which means that 4.6 bits is approximately the number of times the two digits can appear to represent each one of the 26 letters. In that way, entropy is a statistical quantification of how many entities we need to interpret System 1 with entities of System 2.

The concept of entropy used by Prigogine is a measure of the degree of knowledge we have of a system. Its function is to know the current status of any system. In theoretical sense, at the beginning of the universe, entropy was very low; in

**69**

viral information.

postulate too.

*Semiotic Architecture of Viral Data*

*DOI: http://dx.doi.org/10.5772/intechopen.89153*

that returns to the origin of everything [13].

shading off the original meaning until twisting it.

between the relationships of semiotic systems.

lead to cultural and social processes of semiosis.

dissipative structures?

cultures. We are interested in debating two aspects:

other words, a certain type of order governed the beginning of all things. Thus, the evolutionary tendency toward order through disorder becomes a universal reaction

The big question is if human behavior responds to laws of thermodynamics. The hypothesis of this paper postulates that semiosis organizes thoughts as networks, and networks help to dispel entropy and generate order. This happens through an intricate structure of individual and collective relationships. As proposed by Luhmann [19] in his time, we understand communication systems as relations

The new existing analysis of information propagation in virtual environments overcame the impossibility of proofing such hypothesis. Today, it is possible to track the trajectories of information exchange through the topology of these networks, as described by the mathematician Barabási [20] and the physicist Albert [21]. It is also possible to apply Duncan Watts and Steven Strogatz's [22] small world networks, or through the sophisticated methods in Stanley Wasserman and Kethrin Faust's [23] classic book. The postulate "any two people can be connected in a maximum of six steps" of the sociologists Jeffrey Travers, Stanley Milgram [24], and Mark Granovetter [25, 26], is the basis for the applications of modern network theory. Our dissertation comes from this

We postulate that the cascades are a kind of natural dissipative structures in the cultural level. The implication of this postulate is that mechanical laws of nature

This dissertation is argumentative and revolves around communication within

1. Does the difference between personal and collective interpretations result in

2.Does culture generate information cascades to keep its dynamic equilibrium?

For all that has been said so far, readers have in their hands a text that consists of three parts (apart from this introduction and subsequent conclusions). In the first part, we deal with the concept of macroscopic communication level; the second part deals with the microscopic levels of communication; and, finally, we discussed dissipative structures of communication. In this way, the first two parts of this essay are theoretical-methodological; while, the last part, applies the concepts proposed throughout the text to specific cases. We present our preliminary results, to discuss whether it is possible or not to control trends with

In this case, we are talking about digital communication, one of the most ordered systems in the planet. Shannon's information theory establishes that to measure information it is necessary to calculate the range of the data produced by the source. In this approach, quantifying the spread of a text message is the best way to do that task. But Shannon's theory is not designed to explain the changes into meaning [18]. Occasionally, the sense of a message could be switched from its original meaning, by two factors: first, a translation effect, for example, if we do not speak or understand the coding language, and second, an exposition influence. Both factors are context condition of the communication and are not issues from communication theory. The dynamical behavior of meaning in social network has two features: move and stream thoughts. This dual behavior allows expanding or

#### *Semiotic Architecture of Viral Data DOI: http://dx.doi.org/10.5772/intechopen.89153*

*Cognitive and Intermedial Semiotics*

level. The theoretical issue of this kind of behavior is the continuous change of the meaning of the information point-to-point until it becomes fake in opposition to reality. The social importance of this behavior is the impact of the offline world. A lot of massive news turns into political and cultural energy: anger, despair, and polarization. Therefore, the control of digital communication is a topic of political

It should be noted that, with the development of Web 3.0, the semiotic processes have changed. Digital technologies, in addition to providing interaction and updating in real time, stimulate the development of long-range semantic networks, the interaction of large databases, and increasingly efficient algorithms to navigate [4]. This has caused effects or by-products. Super viral information of networks or cascade is the best example of this kind of outgrowths without control. The cascades

are the best example of viral data, and we refer to them in the next pages.

The debate about cascades is if the tendency of information in a network is natural or not. The informal expression of social inclination in digital communication is trending. It refers to a topic currently popular or widely discussed on social

Current studies about digital propaganda have proved that some trendings are controlled by human trolls, bots, and algorithms. Most of them have political and

But in this chapter, we will not go deep into political science. Instead, in the theoretical arena of systems research, Prigogine [13] postulated that dissipative systems are dynamic nonequilibrium open systems with internal gradients. They keep their low entropy condition stable by transporting matter and energy beyond their frontiers. They consume energy and present matter and energy cycles. Dissipative structures develop complexity exporting and dissipating entropy to

The systems we deal in social sciences, humanities, and arts are open systems. Open systems are those that transform one type of energy, matter, or information into another, as they adapt to their environment. The classic mechanic theory defines that in all open systems, change is irreversible. The shifts within open systems generate all kinds of disturbances at the atomic level, which lead to disorder in the molecular structures until the social macrolevel. These variances into the matter, energy, and information are an irreversible process. This process produces a kind of disorder in the fundamental structure and it is measured by its entropy. According to Claude Shannon as Ilya Prigogine, entropy or disorder can be characterized as a statistical measure [13, 17]. Shannon's entropy "is a statistical parameter which measures, in a certain sense, how much information is produced on the average for each letter of a text in the language. If the language is translated into binary digits (0 or 1) in the most efficient way, the entropy H is the average number of binary digits required per letter of the original language" [17]. Our writing system has 26 letters to represent many languages. But if I use my alphabetic keyboard to do a translation to a writing system that only has 2 digits, as binary, I have to count how many times the digits of binary systems I need to combine to reach the best codification. The average of binary system required for each letter is 4.6. The formula is very simple: log2 26 = 4.6 bits per letter, which means that 4.6 bits is approximately the number of times the two digits can appear to represent each one of the 26 letters. In that way, entropy is a statistical quantification of how

many entities we need to interpret System 1 with entities of System 2.

The concept of entropy used by Prigogine is a measure of the degree of knowledge we have of a system. Its function is to know the current status of any system. In theoretical sense, at the beginning of the universe, entropy was very low; in

power than nations and agents take advantage of them.

media websites; they are today's top trending topics.

hybrid warfare purposes [5–12].

their environment [14–16].

**68**

other words, a certain type of order governed the beginning of all things. Thus, the evolutionary tendency toward order through disorder becomes a universal reaction that returns to the origin of everything [13].

In this case, we are talking about digital communication, one of the most ordered systems in the planet. Shannon's information theory establishes that to measure information it is necessary to calculate the range of the data produced by the source. In this approach, quantifying the spread of a text message is the best way to do that task. But Shannon's theory is not designed to explain the changes into meaning [18]. Occasionally, the sense of a message could be switched from its original meaning, by two factors: first, a translation effect, for example, if we do not speak or understand the coding language, and second, an exposition influence. Both factors are context condition of the communication and are not issues from communication theory. The dynamical behavior of meaning in social network has two features: move and stream thoughts. This dual behavior allows expanding or shading off the original meaning until twisting it.

The big question is if human behavior responds to laws of thermodynamics. The hypothesis of this paper postulates that semiosis organizes thoughts as networks, and networks help to dispel entropy and generate order. This happens through an intricate structure of individual and collective relationships. As proposed by Luhmann [19] in his time, we understand communication systems as relations between the relationships of semiotic systems.

The new existing analysis of information propagation in virtual environments overcame the impossibility of proofing such hypothesis. Today, it is possible to track the trajectories of information exchange through the topology of these networks, as described by the mathematician Barabási [20] and the physicist Albert [21]. It is also possible to apply Duncan Watts and Steven Strogatz's [22] small world networks, or through the sophisticated methods in Stanley Wasserman and Kethrin Faust's [23] classic book. The postulate "any two people can be connected in a maximum of six steps" of the sociologists Jeffrey Travers, Stanley Milgram [24], and Mark Granovetter [25, 26], is the basis for the applications of modern network theory. Our dissertation comes from this postulate too.

We postulate that the cascades are a kind of natural dissipative structures in the cultural level. The implication of this postulate is that mechanical laws of nature lead to cultural and social processes of semiosis.

This dissertation is argumentative and revolves around communication within cultures. We are interested in debating two aspects:


For all that has been said so far, readers have in their hands a text that consists of three parts (apart from this introduction and subsequent conclusions). In the first part, we deal with the concept of macroscopic communication level; the second part deals with the microscopic levels of communication; and, finally, we discussed dissipative structures of communication. In this way, the first two parts of this essay are theoretical-methodological; while, the last part, applies the concepts proposed throughout the text to specific cases. We present our preliminary results, to discuss whether it is possible or not to control trends with viral information.
