Evolutionary Learning Model of Social Networking Services with Diminishing Marginal Utility

Yutaro Miura, Fujio Toriumi, Toshiharu Sugawara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

We propose a model of a social networking service (SNS) with diminishing marginal utility in the framework of evolutionary computing and present our investigation on the effect of diminishing marginal utility on the dominant structure of strategies in all agents. SNSs such as Twitter and Facebook have been growing rapidly, but why they are prospering is unknown. SNSs have the characteristics of a public goods game because they are maintained by users posting many articles that incur some cost and because users can also be free riders, who just read articles. Thus, a number of studies aimed at understanding the conditions or mechanisms that keep social media thriving theoretically by introducing the meta-rewards game, which is a variation of a public goods game. The meta-rewards games assume constant marginal utility, meaning that the rewards by receiving comments increase linearly according to the number of comments, but describing the psychological rewards of humans is often inappropriate. In this paper, we present our modification of the model using the diminishing marginal utility and our comparison of the experimental results with those of the original meta-rewards game. We demonstrate that the structure of dominant strategies of all agents in our game is quite different from that in the original meta-rewards game and is more reasonable to explain the users' behavior in SNSs because their efforts in SNSs are limited even if they have many friends.

Original languageEnglish
Title of host publicationThe Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018
PublisherAssociation for Computing Machinery, Inc
Pages1323-1329
Number of pages7
ISBN (Electronic)9781450356404
DOIs
Publication statusPublished - 2018 Apr 23
Event27th International World Wide Web, WWW 2018 - Lyon, France
Duration: 2018 Apr 232018 Apr 27

Publication series

NameThe Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018

Conference

Conference27th International World Wide Web, WWW 2018
CountryFrance
CityLyon
Period18/4/2318/4/27

Keywords

  • agent network
  • cooperation
  • evolutionary learning
  • prisoner's dilemma
  • social network systems

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

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  • Cite this

    Miura, Y., Toriumi, F., & Sugawara, T. (2018). Evolutionary Learning Model of Social Networking Services with Diminishing Marginal Utility. In The Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018 (pp. 1323-1329). (The Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018). Association for Computing Machinery, Inc. https://doi.org/10.1145/3184558.3191573