About One Approach to Assessing the Social Networks' Users Influence

The paper is devoted to the problem of assessing the influence of members of social network communities. It proposes a method for constructing a social network model based on a weighted directed graph, considering the intensity of previous interactions between users. The article also considers the possibility of using Walsh orthogonal functions to simulate the diffusion of information influences between users of social networks. The authors conclude that this approach allows for obtaining estimates of the influence of individual users and their coalitions. The paper also evaluates the speed characteristics of the corresponding algorithm and discusses promising areas for its use in ranking social network users by influence, as well as for predicting the results of information influences based on simulation modeling.

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Publication Details

Journal
Artificial Societies
Published
2026-01-01
DOI
https://doi.org/10.18254/s207751800036722-3
Primary Topic
Opinion Dynamics and Social Influence
Type
article
Field-Weighted Citation Impact
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article

About One Approach to Assessing the Social Networks' Users Influence

Boris Toropov
Artificial Societies
Opinion Dynamics and Social Influence
article

About One Approach to Assessing the Social Networks' Users Influence

Boris Toropov
article en

Abstract

The paper is devoted to the problem of assessing the influence of members of social network communities. It proposes a method for constructing a social network model based on a weighted directed graph, considering the intensity of previous interactions between users. The article also considers the possibility of using Walsh orthogonal functions to simulate the diffusion of information influences between users of social networks. The authors conclude that this approach allows for obtaining estimates of the influence of individual users and their coalitions. The paper also evaluates the speed characteristics of the corresponding algorithm and discusses promising areas for its use in ranking social network users by influence, as well as for predicting the results of information influences based on simulation modeling.

Artificial SocietiesVol. 21(1)
Academy of Management of the Interior Ministry of Russia (RU)
Reduced inequalities
Openalex Percentile: Top 10%
Opinion Dynamics and Social Influence
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About One Approach to Assessing the Social Networks' Users Influence — Boris Toropov · Artificial Societies (2026) | TGRS Research Map | TGRS