TY - GEN
T1 - Evolutionary Learning Model of Social Networking Services with Diminishing Marginal Utility
AU - Miura, Yutaro
AU - Toriumi, Fujio
AU - Sugawara, Toshiharu
N1 - Publisher Copyright:
© 2018 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC BY 4.0 License.
PY - 2018/4/23
Y1 - 2018/4/23
N2 - 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.
AB - 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.
KW - agent network
KW - cooperation
KW - evolutionary learning
KW - prisoner's dilemma
KW - social network systems
UR - http://www.scopus.com/inward/record.url?scp=85070592376&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85070592376&partnerID=8YFLogxK
U2 - 10.1145/3184558.3191573
DO - 10.1145/3184558.3191573
M3 - Conference contribution
AN - SCOPUS:85070592376
T3 - The Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018
SP - 1323
EP - 1329
BT - The Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018
PB - Association for Computing Machinery, Inc
T2 - 27th International World Wide Web, WWW 2018
Y2 - 23 April 2018 through 27 April 2018
ER -