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Love All, Trust a Few: Link Prediction for Trust and Psycho-social Factors in MMOs

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNISA,volume 7227)

Abstract

Massively Multiplayer Online Games (MMOGs) where millions of people can interact with one another have been described as mirrors of human societies and offer excellent venues to analyze human behavior at both the psychological as well as the social level. Within the context of predictive analysis (link prediction as a classification task) in MMOGs, the connection between psycho-sociological theories of communication networks. A mapping of how various elements of trust and other social interactions (mentoring, adversarial relationship, trade) relate to prediction tasks is also established. Results from classification experiments indicate that social environments affect prediction tasks in cooperative vs. adversarial environments in MMOGs and the implications of these results for generalizability of link prediction algorithms is also analyzed.

Keywords

  • Trust in social networks
  • Prediction and Psycho-Social Theories
  • Adversarial environments
  • MMOs

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© 2012 Springer-Verlag Berlin Heidelberg

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Ahmad, M.A., Borbora, Z., Srivastava, J., Contractor, N. (2012). Love All, Trust a Few: Link Prediction for Trust and Psycho-social Factors in MMOs. In: Yang, S.J., Greenberg, A.M., Endsley, M. (eds) Social Computing, Behavioral - Cultural Modeling and Prediction. SBP 2012. Lecture Notes in Computer Science, vol 7227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29047-3_15

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  • DOI: https://doi.org/10.1007/978-3-642-29047-3_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29046-6

  • Online ISBN: 978-3-642-29047-3

  • eBook Packages: Computer ScienceComputer Science (R0)