Going out of business: Auction house behavior in the Massively Multi-player Online Game Glitch

Anders Drachen*, Joseph Riley, Shawna Baskin, Diego Klabjan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


The in-game economies of Massively Multi-player Online Games are complex systems that have to be carefully designed and managed. This paper presents the results of an analysis of auction house data from the Massively Multi-player Online Games Glitch, across a 14. month period, the entire lifetime of the game. The data comprise almost 3. million data points, covering over 20,000 unique players and more than 650 products. Furthermore, an interactive visualization, based on Sankey flow diagrams, is presented which shows the proportion of the different clusters across each time bin, as well as the flow of players between clusters. The diagram allows evaluation of migration of players between clusters as a function of time, as well as a churn analysis. The presented work provides a template analysis and visualization model for progression-based or temporal-based analysis of player behavior broadly applicable to digital games.

Original languageEnglish (US)
Pages (from-to)219-232
Number of pages14
JournalEntertainment Computing
Issue number4
StatePublished - Sep 16 2014


  • Auction house
  • Business intelligence
  • Game analytics
  • Game economy
  • Player behavior

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction


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