ADAPTATION OF THE KURAMOTO MODEL FOR THE ANALYSIS OF THE DISTRIBUTION OF INFORMATION IN SOCIAL NETWORKS
DOI:
https://doi.org/10.28925/2663-4023.2023.21.309314Keywords:
Kuramoto model; dissemination of information; social networks; synchronization; heterogeneous networks; information flows; dynamic systems.Abstract
The article proposes an approach to modification of the Kutemoto model, which allows it to be used to analyze the dissemination of information on social networks, which, in turn, provides an opportunity to study such phenomena as consensus formation when groups of users converge in common opinion, dissemination of innovation and public formation thoughts on a certain reason. The simplified and classic approaches to modeling interactions between users are presented, where oscillators symbolize individual participants, and their frequencies - the current state of information. The frequency can display the initial opinion of the user, when the closer frequencies of the two users, the closer their initial views, and the tendency to change the thought, when the greater the amplitude of oscillations, the more the user is inclined to change his opinion under the influence of others. The main parameters of the model are the communication force (how much one user affects another), the frequency of natural vibrations (the user's initial opinion), noise (random factors that can influence the user's opinion).The advantages of each model for different networking scenarios are highlighted.The classic model used to describe synchronization in dynamic systems is used to study the interaction between social network users. The modified model takes into account the individual properties of users, their pace of information dissemination and the nature of interaction with other network participants. For more accurate modeling of social processes, the model of the Krankmoto can be expanded by taking into account the heterogeneity of users, as different users may have different tendency to influence and different number of connections, introduction of dynamic connections, since the structure of the social network may change over time, and take into account the heterogeneity information in the context of its impact on users.
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