Mining for gold farmers: Automatic detection of deviant players in MMOGs

Muhammad Aurangzeb Ahmad, Brian Keegan, Jaideep Srivastava, Dmitri Williams, Noshir Contractor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

54 Scopus citations

Abstract

Gold farming refers to the illicit practice of gathering and selling virtual goods in online games for real money. Although around one million gold farmers engage in gold farming related activities [14], to date a systematic study of identifying gold farmers has not been done. In this paper we use data from the massively-multiplayer online role-playing game (MMORPG) EverQuest II to identify gold farmers. We perform an exploratory logistic regression analysis to identify salient descriptive statistics followed by a machine learning binary classification problem to identify a set of features for classification purposes. Given the cost associated with investigating gold farmers, we also give criteria for evaluating gold farming detection techniques, and provide suggestions for future testing and evaluation techniques

Original languageEnglish (US)
Title of host publicationProceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009 - 2009 IEEE International Conference on Social Computing, SocialCom 2009
Pages340-345
Number of pages6
DOIs
StatePublished - 2009
Event2009 IEEE International Conference on Social Computing, SocialCom 2009 - Vancouver, BC, Canada
Duration: Aug 29 2009Aug 31 2009

Publication series

NameProceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009
Volume4

Other

Other2009 IEEE International Conference on Social Computing, SocialCom 2009
Country/TerritoryCanada
CityVancouver, BC
Period8/29/098/31/09

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software

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