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Conflict and Computation on Wikipedia: A Finite-State Machine Analysis of Editor Interactions

Author

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  • Simon DeDeo

    (Center for Complex Networks and Systems Research, Department of Informatics, Indiana University, 919 E 10th St, Bloomington, IN 47408, USA
    Program in Cognitive Science, Indiana University, 1900 E 10th St, Bloomington, IN 47406, USA
    Ostrom Workshop in Political Theory and Policy Analysis, 513 N Park Avenue, Bloomington, IN 47408, USA
    Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA)

Abstract

What is the boundary between a vigorous argument and a breakdown of relations? What drives a group of individuals across it? Taking Wikipedia as a test case, we use a hidden Markov model to approximate the computational structure and social grammar of more than a decade of cooperation and conflict among its editors. Across a wide range of pages, we discover a bursty war/peace structure where the systems can become trapped, sometimes for months, in a computational subspace associated with significantly higher levels of conflict-tracking “revert” actions. Distinct patterns of behavior characterize the lower-conflict subspace, including tit-for-tat reversion. While a fraction of the transitions between these subspaces are associated with top-down actions taken by administrators, the effects are weak. Surprisingly, we find no statistical signal that transitions are associated with the appearance of particularly anti-social users, and only weak association with significant news events outside the system. These findings are consistent with transitions being driven by decentralized processes with no clear locus of control. Models of belief revision in the presence of a common resource for information-sharing predict the existence of two distinct phases: a disordered high-conflict phase, and a frozen phase with spontaneously-broken symmetry. The bistability we observe empirically may be a consequence of editor turn-over, which drives the system to a critical point between them.

Suggested Citation

  • Simon DeDeo, 2016. "Conflict and Computation on Wikipedia: A Finite-State Machine Analysis of Editor Interactions," Future Internet, MDPI, vol. 8(3), pages 1-23, July.
    • Handle: RePEc:gam:jftint:v:8:y:2016:i:3:p:31-:d:73586
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    References listed on IDEAS

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    1. Sam Ransbotham & Gerald C. Kane & Nicholas H. Lurie, 2012. "Network Characteristics and the Value of Collaborative User-Generated Content," Marketing Science, INFORMS, vol. 31(3), pages 387-405, May.
    2. Gilles Celeux & Jean-Baptiste Durand, 2008. "Selecting hidden Markov model state number with cross-validated likelihood," Computational Statistics, Springer, vol. 23(4), pages 541-564, October.
    3. Simon DeDeo & David C Krakauer & Jessica C Flack, 2010. "Inductive Game Theory and the Dynamics of Animal Conflict," PLOS Computational Biology, Public Library of Science, vol. 6(5), pages 1-16, May.
    4. Elizabeth A Hobson & Simon DeDeo, 2015. "Social Feedback and the Emergence of Rank in Animal Society," PLOS Computational Biology, Public Library of Science, vol. 11(9), pages 1-20, September.
    5. Mills,Terence C., 1991. "Time Series Techniques for Economists," Cambridge Books, Cambridge University Press, number 9780521405744.
    6. Samer Faraj & Sirkka L. Jarvenpaa & Ann Majchrzak, 2011. "Knowledge Collaboration in Online Communities," Organization Science, INFORMS, vol. 22(5), pages 1224-1239, October.
    7. S. Bacci & S. Pandolfi & F. Pennoni, 2014. "A comparison of some criteria for states selection in the latent Markov model for longitudinal data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(2), pages 125-145, June.
    8. Bradi Heaberlin & Simon DeDeo, 2016. "The Evolution of Wikipedia’s Norm Network," Future Internet, MDPI, vol. 8(2), pages 1-21, April.
    9. Gerald C. Kane & Jeremiah Johnson & Ann Majchrzak, 2014. "Emergent Life Cycle: The Tension Between Knowledge Change and Knowledge Retention in Open Online Coproduction Communities," Management Science, INFORMS, vol. 60(12), pages 3026-3048, December.
    10. Jessica C. Flack & Michelle Girvan & Frans B. M. de Waal & David C. Krakauer, 2006. "Policing stabilizes construction of social niches in primates," Nature, Nature, vol. 439(7075), pages 426-429, January.
    11. Pamela J. Hinds & Diane E. Bailey, 2003. "Out of Sight, Out of Sync: Understanding Conflict in Distributed Teams," Organization Science, INFORMS, vol. 14(6), pages 615-632, December.
    12. Rong Wang & John A. Dearing & Peter G. Langdon & Enlou Zhang & Xiangdong Yang & Vasilis Dakos & Marten Scheffer, 2012. "Flickering gives early warning signals of a critical transition to a eutrophic lake state," Nature, Nature, vol. 492(7429), pages 419-422, December.
    13. 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.
    14. Marten Scheffer & Jordi Bascompte & William A. Brock & Victor Brovkin & Stephen R. Carpenter & Vasilis Dakos & Hermann Held & Egbert H. van Nes & Max Rietkerk & George Sugihara, 2009. "Early-warning signals for critical transitions," Nature, Nature, vol. 461(7260), pages 53-59, September.
    15. Albert-László Barabási, 2005. "The origin of bursts and heavy tails in human dynamics," Nature, Nature, vol. 435(7039), pages 207-211, May.
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