Going Out of Business: Auction House Behavior in the Massively Multi-Player Online Game
This provides a template for analyzing and visualizing temporal player behavior in games, but it is incremental as it applies existing methods to new data.
The paper analyzed auction house data from the MMOG Glitch over its entire 14-month lifetime, comprising nearly 3 million data points, 20,000 players, and 650 products, and presented an interactive Sankey diagram visualization to track player cluster migration and churn over time.
The in-game economies of massively multi-player online games (MMOGs) 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 MMOG Glitch, across a 14 month time period, the entire lifetime of the game. The data comprise almost 3 million data points, 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 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 games.