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Information Communities in Social Networks. Part I: From Concept to Mathematical Modelsстатья
- Авторы: Губанов Д.А., Петров И.В.
- Журнал: Control Sciences
- Том: 1
- Год издания: 2021
- Издательство: Институт проблем управления им. В.А. Трапезникова РАН
- Местоположение издательства: Москва
- Первая страница: 13
- Последняя страница: 20
- DOI: 10.25728/cs.2021.1.2
- Аннотация: This survey covers the literature related to information communities in mutually complementary areas: the formation of information communities in social networks and some applied aspects of identifying and analyzing information communities in social networks. First, mathematical models describing the formation of information communities under uncertainty are considered. Among these models, the most relevant ones are the mathematical models of opinion/belief dynamics reflecting any changes in the beliefs of nodes under the influence of other network nodes and significant effects (in particular, the preservation of differences in beliefs and the divergence of beliefs) that lead to the formation of information communities. In part I of the survey, the concept of an information community is first presented. Then infor-mation processing and decision-making by an agent in a social network under external uncer-tainty are outlined. The factors influencing the formation of information communities in the network are highlighted, and the basic models of Bayesian agents and their extensions are investigated.
- Добавил в систему: Губанов Дмитрий Алексеевич