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A hybrid epidemic model for deindividuation and antinormative behavior in online social networks

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Abstract

With the increasing popularity of user-contributed sites, the phenomenon of “social pollution”, the presence of abusive posts has become increasingly prevalent. In this paper, we describe a novel approach to investigate negative behavior dynamics in online social networks as epidemic phenomena. We show that using hybrid automata, it is possible to explain the contagion of antinormative behavior in certain online commentaries. We present two variations of a finite-state machine model for time-varying epidemic dynamics, namely triggered state transition and iterative local regression, which differ with respect to accuracy and complexity.We validate the model with experiments over a dataset of 400,000 comments on 800 YouTube videos, classified by genre, and indicate how different epidemic patterns of behavior can be tied to specific interaction patterns among users.

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Notes

  1. For simplicity, we assume that comment ratings are not the product of up-voting by trolls or spammers.

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Acknowledgments

Portions of Dr. Griffin’s, Dr. Squicciarini’s and Dr. Rajtmajer’s work were supported by the Army Research Office under Grant W911NF-13-1-0271. Portions of Dr. Squicciarini’s work were additionally supported by the Air Force Office of Scientific Research, Grant Number FA9550-15-1-0149.

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Authors and Affiliations

  1. College of Information Sciences and Technology, Pennsylvania State University, State College, USA

    Cong Liao & Anna Squicciarini

  2. Department of Mathematics, United States Naval Academy, Annapolis, USA

    Christopher Griffin

  3. Department of Mathematics, Pennsylvania State University, State College, USA

    Sarah Rajtmajer

Authors
  1. Cong Liao
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  2. Anna Squicciarini
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  3. Christopher Griffin
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  4. Sarah Rajtmajer
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Correspondence to Sarah Rajtmajer.

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Liao, C., Squicciarini, A., Griffin, C. et al. A hybrid epidemic model for deindividuation and antinormative behavior in online social networks. Soc. Netw. Anal. Min. 6, 13 (2016). https://doi.org/10.1007/s13278-016-0321-5

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  • DOI: https://doi.org/10.1007/s13278-016-0321-5

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