**4.2 Barabási-Albert model implementation**

The suggested algorithm was implemented using a random scale-free network generated by Barabási-Albert algorithm. The network consisted of 1000 nods. The results are given in **Figure 6**. The automaton was tested in the following way: the initial values were distributed following the normal distribution law; 90 random initiators of the IPI and 10 opponents were selected out of all the subjects; the automaton was tested 100 times, each test run including 300 steps; average number of subjects in each of the states was determined. The initial personal opinion of the subject *Vk* about the information was distributed according to the normal distribution rule within the intervals [�1; �0.5], [�0.5; 0.5], [0.5; 1]. Trust level *TRkj TI* was distributed according to the normal distribution rule within the interval [0; 1] or [�1; 1]. **Figures 7**–**9** demonstrate the functioning of the automaton.

**Figure 7** demonstrates the functioning of the automaton, when *Vk* ∈½ � �0*;* 5; 0*;* 5 , that is, most subjects are neutral to the IPI. **Figure 8** demonstrates the functioning of the automaton, when *Vk* ∈½ � �1; �0*;* 5 , that is, most subjects are negative to the IPI. **Figure 9** demonstrates the functioning of the automaton, when *Vk* ∈½ � 0*;* 5; 1 , that is, most subjects are positive to the IPI. Figures "a" demonstrate the functioning of the automaton, when *TRkj TI* <sup>∈</sup> ½ � <sup>0</sup>; <sup>1</sup> , that is, the subjects adopt opinions of

**Figure 5.**

the value of information diffusion equal 1 spread the information to the

A cell may change its state receiving influence *Fi* from the neighbouring cells whose information transfer value equals 1. When the influence is received, the current values of opinion *Vk* and information diffusion *Rk* are calculated.

The suggested algorithm was implemented on a 100 � 100 grid. The automaton was tested in the following way: the initial values were distributed following the normal distribution law; 10 random initiators of the IPI and 2 opponents were selected out of all the subjects; the automaton was tested 100 times, each test run including 1000 steps; average number of subjects in each of the states was determined. The initial personal opinion of subject *Vk* about the information was distributed according to the normal distribution rule within the intervals [�1; �0.5],

distribution rule within the interval [0; 1] or [�1; 1]. **Figures 3**–**5** demonstrate the

other subjects. Figures "b" demonstrate the functioning of the automaton, when

*Distribution of cells according to the discrete time whenever Vk* ∈½ � �0*;* 5; 0*;* 5 *.*

*Distribution of cells according to the discrete time whenever Vk* ∈½ � �1; �0*;* 5 *.*

*TI* <sup>∈</sup> ½ � �1; <sup>1</sup> , that is, the subject has the opposite opinion to the one imposed

**Figure 4** demonstrates the functioning of the automaton, when *Vk* ∈½ � �0*;* 5; 0*;* 5 , that is, most subjects are neutral to the IPI. **Figure 5** demonstrates the functioning of the automaton, when *Vk* ∈½ � �1; �0*;* 5 , that is, most subjects are negative to the IPI. **Figure 6** demonstrates the functioning of the automaton, when *Vk* ∈½ � 0*;* 5; 1 , that is, most subjects are positive to the IPI. Figures "a" demonstrate the function-

*TI* was distributed according to the normal

*TI* <sup>∈</sup> ½ � <sup>0</sup>; <sup>1</sup> , that is, the subjects adopt opinions of

neighbouring cells.

**4. Experiments and discussion**

*Probability, Combinatorics and Control*

[�0.5; 0.5], [0.5; 1]. Trust level *TRkj*

functioning of the automaton.

ing of the automaton, when *TRkj*

*TRkj*

by the IPI.

**Figure 3.**

**Figure 4.**

**302**

**4.1 Two-dimensional array implementation**

*Distribution of cells according to the discrete time whenever Vk* ∈½ � 0*;* 5; 1 *.*

**Figure 6.** *Random scale-free network generated by Barabási-Albert model.*

when the subjects do not trust each other and change their opinions to the opposite ones (**Figures 3**–**5b** and **7**–**9b**), the number of subjects in states S3

in Refs. [4, 5, 30]. These works consider the information diffusion, which is an individual case of IPI diffusion in social networks. As opposed to Refs. [4, 5, 30, 39, 40], the suggested model is not based on the probabilistic characteristics of the subjects of the social network but takes into account the social and psychological parameters of the subjects and their psychological state during IPI diffusion in social

The results obtained using the suggested models agree with the results presented

The paper suggests a model for describing the diffusion process of information-

, Pavel Parinov<sup>1</sup>

2 Voronezh Institute of the Federal Penitentiary Service of Russia, Voronezh, Russia

© 2019 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,

3 National Research University of Electronic Technology, Moscow, Russia

, Sergey Kochedykov<sup>2</sup> and

psychological impact in social networks based on cellular automata. Cellular automata models can change the states of a large number of cells over a minimal period of time, which is very useful for the modelling of the process of informationpsychological impact diffusion in social networks. The suggested models can thus represent the process of IPI diffusion in a social network and the corresponding changes in the opinions of its subjects caused by their immediate neighbours, taking

and S4 is similar, irrespective of their initial state.

*Modelling the Information-Psychological Impact in Social Networks*

*DOI: http://dx.doi.org/10.5772/intechopen.88252*

into account social and psychological factors.

\*, Nikita Goncharov<sup>1</sup>

\*Address all correspondence to: goncharov@infobez.org

1 JSC "NGO" Infosecurity, Voronezh, Russia

provided the original work is properly cited.

networks.

**5. Conclusion**

**Author details**

Igor Goncharov<sup>1</sup>

**305**

Alexander Dushkin<sup>3</sup>

**Figure 7.** *Distribution of cells according to the discrete time whenever Vk* ∈½ � �0*;* 5; 0*;* 5 *.*

**Figure 8.**

*Distribution of cells according to the discrete time whenever Vk* ∈½ � �1; �0*;* 5 *.*

**Figure 9.**

*Distribution of cells according to the discrete time whenever Vk* ∈½ � 0*;* 5; 1 *.*

other subjects. Figures "b" demonstrate the functioning of the automaton, when *TRkj TI* <sup>∈</sup> ½ � �1; <sup>1</sup> , that is, the subject has the opposite opinion to the one imposed by the IPI.
