An evolutionary game model for the spread of non-cooperative behavior in online social networks

Sarah Rajtmajer; Christopher Griffin; Derek Mikesell; Anna Squicciarini

doi:10.1145/2695664.2695867

An evolutionary game model for the spread of non-cooperative behavior in online social networks

College of Information Sciences and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

We present an evolutionary game-theoretic model for the spread of non-cooperative behavior in online social networks. We formulate a two-strategy game wherein each player's behavior is classified as normal (cooperate) or abusive (defect) and pairwise interactions between adjacent players in the network graph yield a unique payoff to each according a prisoner's dilemma payoff structure. Player strategies evolve by imitation of successful behavior in observable neighborhoods. We demonstrate convergence of player behavior over time to a final strategy vector. Proof-of-concept is given for a real-world dataset collected from a popular online forum.

Original language	English (US)
Title of host publication	2015 Symposium on Applied Computing, SAC 2015
Editors	Dongwan Shin
Publisher	Association for Computing Machinery
Pages	1154-1159
Number of pages	6
ISBN (Electronic)	9781450331968
DOIs	https://doi.org/10.1145/2695664.2695867
State	Published - Apr 13 2015
Event	30th Annual ACM Symposium on Applied Computing, SAC 2015 - Salamanca, Spain Duration: Apr 13 2015 → Apr 17 2015

Publication series

Name	Proceedings of the ACM Symposium on Applied Computing
Volume	13-17-April-2015

Other

Other	30th Annual ACM Symposium on Applied Computing, SAC 2015
Country/Territory	Spain
City	Salamanca
Period	4/13/15 → 4/17/15

All Science Journal Classification (ASJC) codes

Software

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10.1145/2695664.2695867

Cite this

Rajtmajer, S., Griffin, C., Mikesell, D., & Squicciarini, A. (2015). An evolutionary game model for the spread of non-cooperative behavior in online social networks. In D. Shin (Ed.), 2015 Symposium on Applied Computing, SAC 2015 (pp. 1154-1159). (Proceedings of the ACM Symposium on Applied Computing; Vol. 13-17-April-2015). Association for Computing Machinery. https://doi.org/10.1145/2695664.2695867

@inproceedings{86f777afa35f4f10890355b53700a801,

title = "An evolutionary game model for the spread of non-cooperative behavior in online social networks",

abstract = "We present an evolutionary game-theoretic model for the spread of non-cooperative behavior in online social networks. We formulate a two-strategy game wherein each player's behavior is classified as normal (cooperate) or abusive (defect) and pairwise interactions between adjacent players in the network graph yield a unique payoff to each according a prisoner's dilemma payoff structure. Player strategies evolve by imitation of successful behavior in observable neighborhoods. We demonstrate convergence of player behavior over time to a final strategy vector. Proof-of-concept is given for a real-world dataset collected from a popular online forum.",

author = "Sarah Rajtmajer and Christopher Griffin and Derek Mikesell and Anna Squicciarini",

year = "2015",

month = apr,

day = "13",

doi = "10.1145/2695664.2695867",

language = "English (US)",

series = "Proceedings of the ACM Symposium on Applied Computing",

publisher = "Association for Computing Machinery",

pages = "1154--1159",

editor = "Dongwan Shin",

booktitle = "2015 Symposium on Applied Computing, SAC 2015",

}

Rajtmajer, S , Griffin, C, Mikesell, D & Squicciarini, A 2015, An evolutionary game model for the spread of non-cooperative behavior in online social networks. in D Shin (ed.), 2015 Symposium on Applied Computing, SAC 2015. Proceedings of the ACM Symposium on Applied Computing, vol. 13-17-April-2015, Association for Computing Machinery, pp. 1154-1159, 30th Annual ACM Symposium on Applied Computing, SAC 2015, Salamanca, Spain, 4/13/15. https://doi.org/10.1145/2695664.2695867

An evolutionary game model for the spread of non-cooperative behavior in online social networks. / Rajtmajer, Sarah ; Griffin, Christopher; Mikesell, Derek et al.
2015 Symposium on Applied Computing, SAC 2015. ed. / Dongwan Shin. Association for Computing Machinery, 2015. p. 1154-1159 (Proceedings of the ACM Symposium on Applied Computing; Vol. 13-17-April-2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - An evolutionary game model for the spread of non-cooperative behavior in online social networks

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N2 - We present an evolutionary game-theoretic model for the spread of non-cooperative behavior in online social networks. We formulate a two-strategy game wherein each player's behavior is classified as normal (cooperate) or abusive (defect) and pairwise interactions between adjacent players in the network graph yield a unique payoff to each according a prisoner's dilemma payoff structure. Player strategies evolve by imitation of successful behavior in observable neighborhoods. We demonstrate convergence of player behavior over time to a final strategy vector. Proof-of-concept is given for a real-world dataset collected from a popular online forum.

AB - We present an evolutionary game-theoretic model for the spread of non-cooperative behavior in online social networks. We formulate a two-strategy game wherein each player's behavior is classified as normal (cooperate) or abusive (defect) and pairwise interactions between adjacent players in the network graph yield a unique payoff to each according a prisoner's dilemma payoff structure. Player strategies evolve by imitation of successful behavior in observable neighborhoods. We demonstrate convergence of player behavior over time to a final strategy vector. Proof-of-concept is given for a real-world dataset collected from a popular online forum.

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DO - 10.1145/2695664.2695867

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BT - 2015 Symposium on Applied Computing, SAC 2015

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T2 - 30th Annual ACM Symposium on Applied Computing, SAC 2015

Y2 - 13 April 2015 through 17 April 2015

ER -

An evolutionary game model for the spread of non-cooperative behavior in online social networks

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