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Modeling Evolutionary Dynamics of Lurking in Social Networks

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Complex Networks VII

Part of the book series: Studies in Computational Intelligence ((SCI,volume 644))

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Abstract

Lurking is a complex user-behavioral phenomenon that occurs in all large-scale online communities and social networks. It generally refers to the behavior characterizing users that benefit from the information produced by others in the community without actively contributing back to the production of social content. The amount and evolution of lurkers may strongly affect an online social environment, therefore understanding the lurking dynamics and identifying strategies to curb this trend are relevant problems. In this regard, we introduce the Lurking Game, i.e., a model for analyzing the transitions from a lurking to a non-lurking (i.e., active) user role, and vice versa, in terms of evolutionary game theory. We evaluate the proposed Lurking Game by arranging agents on complex networks and analyzing the system evolution, seeking relations between the network topology and the final equilibrium of the game. Results suggest that the Lurking Game is suitable to model the lurking dynamics, showing how the adoption of rewarding mechanisms combined with the modeling of hypothetical heterogeneity of users’ interests may lead users in an online community towards a cooperative behavior.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Cagliari, Cagliari, Italy

    Marco A. Javarone

  2. Department of Computer, Modeling, Electronics, and Systems Engineering, University of Calabria, Rende, Italy

    Roberto Interdonato & Andrea Tagarelli

Authors
  1. Marco A. Javarone
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  2. Roberto Interdonato
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  3. Andrea Tagarelli
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Corresponding author

Correspondence to Andrea Tagarelli .

Editor information

Editors and Affiliations

  1. LE2I , UFR Sciences et Techniques, Université de Bourgogne, Dijon, France

    Hocine Cherifi

  2. New York University, Center for Data Science, New York, USA

    Bruno Gonçalves

  3. BioComplex Laboratory, Computer Sciences, Florida Institute of Technology, Melbourne, FL, Florida, USA

    Ronaldo Menezes

  4. 111 Dana, Physics Department, Northeastern University, Boston, Massachusetts, USA

    Roberta Sinatra

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Javarone, M.A., Interdonato, R., Tagarelli, A. (2016). Modeling Evolutionary Dynamics of Lurking in Social Networks. In: Cherifi, H., Gonçalves, B., Menezes, R., Sinatra, R. (eds) Complex Networks VII. Studies in Computational Intelligence, vol 644. Springer, Cham. https://doi.org/10.1007/978-3-319-30569-1_17

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  • DOI: https://doi.org/10.1007/978-3-319-30569-1_17

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