Polarization of opinions in the group: a modeling algorithm considering the dynamics of social bonds

• Published in: Procedia computer science Vol. 213; pp. 596 - 601
• Main Authors: Chebotarev, Vladimir, Andreyuk, Denis, Elizarova, Anastasiya, Ushakov, Vadim
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 2022
• Subjects: consensus; Gephi; group dynamics of opinions; group dynamics of social bonds; modeling; polarization; Python; consensus; group dynamics of social bonds; modeling; group dynamics of opinions; polarization; Gephi; Python
• ISSN: 1877-0509; 1877-0509
• DOI: 10.1016/j.procs.2022.11.108

The dynamics of opinion in a group are of interest for a number of practical purposes. In particular, consensus helps and polarization of opinions hinders cohesive teamwork. Existing approaches for modeling opinion dynamics mostly do not take into account the dynamism of social relations in a group. This paper proposes an algorithm and a program based on it, which allows modeling opinion dynamics considering that the strength of the connection, i.e. the probability of the next contact between two given group members depends on the result of their current communication. As an example, the paper presents the dynamics of opinions and the corresponding dynamics of the strength of bonds for a group of 100 people. With an initial uniform distribution of opinion values, over 50 cycles of interaction the group arrives at an equilibrium state with three subgroups that have opinion values as far apart as possible. The graphs of link dynamics show the formation of stable subgroups as early as after 5 cycles of interaction. The applicability of this model approach to a number of areas of applied and fundamental research is discussed.