Abstract
How users of social networking services (SNSs) dynamically identify their own reasonable strategies was investigated by applying a co-evolutionary algorithm to an agent-based game theoretic model of SNSs. We often use SNSs such as Twitter, Facebook, and Instagram, but we can also freeride without providing any content because providing information incurs costs to us. Numerous studies on evolutionary network analysis have been conducted to investigate why people continue to post articles. In these studies, genetic algorithms (GAs) have often been used to find reasonable strategies for SNS users. Although the evolved strategies in these studies are usually common among all users, the appropriate strategies for them must be diverse because the strategies are used in various circumstances. In this paper, we present our analysis using a co-evolutionary algorithm, multiple-world GA (MWGA), the various strategies for individual agents involving co-evolution with their neighboring agents. We also present the fitness value we obtained, a value that was higher than those obtained using the conventional GA. Finally, we show that the MWGA enables us to observe dynamic processes of co-evolution, i.e., why agents reach their own strategies in different circumstances. This analysis is helpful to understand various users’ behaviors through mutual interactions with neighboring users.
T. Sugawara—This work was partly supported by KAKENHI (17KT0044, 19H02376, 18H03498).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Albert, R., Barabási, A.L.: Statistical mechanics of complex networks. Rev. Mod. Phys. 74, 47–97 (2002). https://doi.org/10.1103/RevModPhys.74.47
Axelrod, R.: An evolutionary approach to norms. Am. Polit. Sci. Rev. 80(4), 1095–1111 (1986)
Ebel, H., Bornholdt, S.: Coevolutionary games on networks. Phys. Rev. E 66(5), 056118 (2002)
Fechner, G.T., Howes, D.H., Boring, E.G.: Elements of Psychophysics, vol. 1. Holt, Rinehart and Winston, New York (1966)
Garcia, D., Mavrodiev, P., Schweitzer, F.: Social resilience in online communities: the autopsy of Friendster. In: Proceedings of the First ACM Conference on Online Social Networks, COSN 2013, pp. 39–50. ACM, New York (2013). https://doi.org/10.1145/2512938.2512946
Hirahara, Y., Toriumi, F., Sugawara, T.: Evolution of cooperation in SNS-norms game on complex networks and real social networks. In: International Conference on Social Informatics, pp. 112–120. Springer (2014)
Lőrincz, L., Koltai, J., Győr, A.F., Takács, K.: Collapse of an online social network: burning social capital to create it? Soc. Netw. 57, 43–53 (2019)
Miura, Y., Toriumi, F., Sugawara, T.: Evolutionary learning model of social networking services with diminishing marginal utility. In: Companion Proceedings of the The Web Conference 2018, WWW 2018, pp. 1323–1329. International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland (2018). https://doi.org/10.1145/3184558.3191573
Miura, Y., Toriumi, F., Sugawara, T.: Multiple world genetic algorithm to analyze individually advantageous behaviors in complex networks. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 297–298. GECCO 2019. ACM, New York (2019). https://doi.org/10.1145/3319619.3321989
Sun, N., Rau, P.P.L., Ma, L.: Understanding lurkers in online communities: a literature review. Comput. Hum. Behav. 38, 110–117 (2014)
Toriumi, F., Yamamoto, H., Okada, I.: Why do people use social media? Agent-based simulation and population dynamics analysis of the evolution of cooperation in social media. In: Proceedings of the 2012 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology-Volume 02, pp. 43–50. IEEE Computer Society (2012)
Vázquez, A.: Growing network with local rules: preferential attachment, clustering hierarchy, and degree correlations. Phys. Rev. E 67(5), 056104 (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Miura, Y., Toriumi, F., Sugawara, T. (2020). Analysis of Diversity and Dynamics in Co-evolution of Cooperation in Social Networking Services. In: Cherifi, H., Gaito, S., Mendes, J., Moro, E., Rocha, L. (eds) Complex Networks and Their Applications VIII. COMPLEX NETWORKS 2019. Studies in Computational Intelligence, vol 881. Springer, Cham. https://doi.org/10.1007/978-3-030-36687-2_41
Download citation
DOI: https://doi.org/10.1007/978-3-030-36687-2_41
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-36686-5
Online ISBN: 978-3-030-36687-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)