Modeling and analyzing users’ behavioral strategies with co-evolutionary process

Yutaro Miura, Fujio Toriumi, Toshiharu Sugawara*

*この研究の対応する著者

研究成果: Article査読

抄録

Social networking services (SNSs) are constantly used by a large number of people with various motivations and intentions depending on their social relationships and purposes, and thus, resulting in diverse strategies of posting/consuming content on SNSs. Therefore, it is important to understand the differences of the individual strategies depending on their network locations and surroundings. For this purpose, by using a game-theoretical model of users called agents and proposing a co-evolutionary algorithm called multiple-world genetic algorithm to evolve diverse strategy for each user, we investigated the differences in individual strategies and compared the results in artificial networks and those of the Facebook ego network. From our experiments, we found that agents did not select the free rider strategy, which means that just reading the articles and comments posted by other users, in the Facebook network, although this strategy is usually cost-effective and usually appeared in the artificial networks. We also found that the agents who mainly comment on posted articles/comments and rarely post their own articles appear in the Facebook network but do not appear in the connecting nearest-neighbor networks, although we think that this kind of user actually exists in real-world SNSs. Our experimental simulation also revealed that the number of friends was a crucial factor to identify users’ strategies on SNSs through the analysis of the impact of the differences in the reward for a comment on various ego networks.

本文言語English
論文番号11
ジャーナルComputational Social Networks
8
1
DOI
出版ステータスPublished - 2021 12

ASJC Scopus subject areas

  • 情報システム
  • モデリングとシミュレーション
  • 人間とコンピュータの相互作用
  • コンピュータ サイエンスの応用

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