PROCESS MODELING OF MESSAGE DISTRIBUTION IN SOCIAL NETWORKS BASED ON SOCIO-COMMUNICATIVE SOLITONS

Andrii Bomba,Yuriy Turbal,Nataliia Kunanets,Volodymyr Pasichnyk

doi:10.47839/ijc.17.4.1147

Abstract

The article proposes a new class of models for distributing messages in social networks based on socio- communicative solitons. This class of models allows to take into account the specific mechanisms for transmitting messages in the chains of the network graph, in which each of the vertices are individuals who, receiving a message, initially form their attitude towards it, and then decide on the further transmission of this message, provided that the corresponding potential of the interaction of two individuals exceeds a certain threshold level. The authors developed the original algorithm for calculating the time moments of message distribution in the corresponding chain, which comes to the solution of a series of Cauchy problems for systems of ordinary nonlinear differential equations. A special continualization procedure is formulated, which makes it possible to simplify substantially the resulting system of equations and replace a part of the equations by the Boussinesq or Korteweg-de Vries equations. The presence of soliton solutions to the above-mentioned equations provides grounds for considering socio-communicative solitons as an effective tool for modeling the processes of distributing messages in social networks and investigating the diverse influences on their dissemination processes.

Highlights

The creation of the Internet and the launch of a wide range of social networks on its basis has led to a series of information and technological revolutionary transformations in society and has generated a number of new challenges both in the humanities and in the field of data analysis, mathematical modeling, physics, computer technology, etc. [2, 5,6,7]
The conducted analysis confirms the validity of the assertion that all models should be divided according to the level of refinement into the corpuscular models, in which it is possible to identify an individual for certain multiple characteristics and generalized models describing the characteristics of groups of individuals or the community as a whole, and which allow us to form general ideas of processes of message distribution or public opinion formation, etc
Corpuscular models include a number of models that use cellular automata [18, 24], cascading models of various types [13], models of network autocorrelation [3], adaptive and imitation behavior model [12], “Game Name” model [18], quantum models, which are similar to Ising models [26, 27]

Summary

Introduction

The creation of the Internet and the launch of a wide range of social networks on its basis has led to a series of information and technological revolutionary transformations in society and has generated a number of new challenges both in the humanities and in the field of data analysis, mathematical modeling, physics, computer technology, etc. [2, 5,6,7]. The most important process that is implemented in social networks is the message dissemination that significantly affects both the attitudes and behavior of individuals and the formation of public opinion of groups and communities on certain issues. This is an effective motive for the creation of new models, which in a large number have appeared in recent years; authors considering models for distributing messages [9,10] and models for forming the opinions of both individuals and communities in general [13,14,15,16]. Corpuscular models include a number of models that use cellular automata [18, 24], cascading models of various types [13], models of network autocorrelation [3], adaptive and imitation behavior model [12], “Game Name” model [18], quantum models, which are similar to Ising models [26, 27]

Objectives

Methods

Conclusion