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Social Dynamics In A Large-Scale Online Game

Author

Listed:
  • MICHAEL SZELL

    (Section for Science of Complex Systems, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria)

  • STEFAN THURNER

    (Section for Science of Complex Systems, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria;
    Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA;
    IIASA, Schlossplatz 1, 2361 Laxenburg, Austria)

Abstract

Complex systems — when treated as systems accessible to natural sciences — pose tremendous requirements on data. Usually these requirements obstruct a scientific understanding of social phenomena on scientific grounds. Due to developments in IT, new collective human behavior, new dimensions of data sources are beginning to open up. Here we report on a complete data set of an entire society, consisting of over 350,000 human players of a massive multiplayer online game. All actions of all players over three years are recorded, including communication behavior and social ties. In this work we review the first steps undertaken in analyzing this vast data set, focusing on social dynamics on friend-, enemy- and communication networks. This new data-driven approach to social science allows to study socio-economic behavior of humans and human groups in specific environments with unprecedented precision. We propose two new empirical social laws which relate the network properties of link weight, overlap and betweenness centrality in a nonlinear way, and provide strong quantitative evidence for classical social balance assumptions, the weak ties hypothesis and triadic closure. In our analysis of large-scale multirelational networks we discover systematic deviations between positive and negative tie networks. Exploring such virtual "social laboratories" in the light of complexity science has the potential to lead to the discovery of systemic properties of human societies, with unforeseen impact on managing human-induced crises.

Suggested Citation

  • Michael Szell & Stefan Thurner, 2012. "Social Dynamics In A Large-Scale Online Game," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(06), pages 1-18.
    • Handle: RePEc:wsi:acsxxx:v:15:y:2012:i:06:n:s0219525912500646
    DOI: 10.1142/S0219525912500646
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    References listed on IDEAS

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    1. Taha Yasseri & Robert Sumi & András Rung & András Kornai & János Kertész, 2012. "Dynamics of Conflicts in Wikipedia," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-12, June.
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    Cited by:

    1. Young Bin Kim & Sang Hyeok Lee & Shin Jin Kang & Myung Jin Choi & Jung Lee & Chang Hun Kim, 2015. "Virtual World Currency Value Fluctuation Prediction System Based on User Sentiment Analysis," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-18, August.
    2. Michael Szell & Sébastian Grauwin & Carlo Ratti, 2014. "Contraction of Online Response to Major Events," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-9, February.
    3. Maximilian Sadilek & Peter Klimek & Stefan Thurner, 2018. "Asocial balance—how your friends determine your enemies: understanding the co-evolution of friendship and enmity interactions in a virtual world," Journal of Computational Social Science, Springer, vol. 1(1), pages 227-239, January.
    4. Evangelos Ioannidis & Nikos Varsakelis & Ioannis Antoniou, 2020. "Promoters versus Adversaries of Change: Agent-Based Modeling of Organizational Conflict in Co-Evolving Networks," Mathematics, MDPI, vol. 8(12), pages 1-25, December.
    5. Young Bin Kim & Kyeongpil Kang & Jaegul Choo & Shin Jin Kang & TaeHyeong Kim & JaeHo Im & Jong-Hyun Kim & Chang Hun Kim, 2017. "Predicting the Currency Market in Online Gaming via Lexicon-Based Analysis on Its Online Forum," Complexity, Hindawi, vol. 2017, pages 1-10, December.

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