Guilt by association? Network based propagation approaches for gold farmer detection. Ahmad, M., A., Keegan, B., Roy, A., Williams, D., Srivastava, J., & Contractor, N. Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013, 2013.
doi  abstract   bibtex   
The term 'Gold Farmer' refers to a class of players in massive online games (MOGs) involved in a set of interrelated activities which are considered to be deviant activities. Consequently these gold farmers are actively banned by game administrators.The task of gold farmer detection is to identify gold farmers in a population of players but just like other clandestine actors they not labeled as such. In this paper the problem of extending the label of gold farmers to players which are not labeled as such is considered. Two main classes of techniques are described and evaluated: Network-based approaches and similarity based approaches. It is also explored how dividing the problem further by relabeling the data based on behavioral patterns can further improve the results Copyright 2013 ACM.
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 title = {Guilt by association? Network based propagation approaches for gold farmer detection},
 type = {article},
 year = {2013},
 pages = {121-126},
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 abstract = {The term 'Gold Farmer' refers to a class of players in massive online games (MOGs) involved in a set of interrelated activities which are considered to be deviant activities. Consequently these gold farmers are actively banned by game administrators.The task of gold farmer detection is to identify gold farmers in a population of players but just like other clandestine actors they not labeled as such. In this paper the problem of extending the label of gold farmers to players which are not labeled as such is considered. Two main classes of techniques are described and evaluated: Network-based approaches and similarity based approaches. It is also explored how dividing the problem further by relabeling the data based on behavioral patterns can further improve the results Copyright 2013 ACM.},
 bibtype = {article},
 author = {Ahmad, Muhammad Aurangzeb and Keegan, Brian and Roy, Atanu and Williams, Dmitri and Srivastava, Jaideep and Contractor, Noshir},
 doi = {10.1145/2492517.2492649},
 journal = {Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013}
}

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