Going Out of Business: Auction House Behavior in the Massively Multi-Player Online Game

TL;DR

This study analyzes auction house data from the MMOG Glitch over 14 months, revealing player behavior patterns, migration, and churn, and introduces visualization tools for game economy analysis.

Contribution

It provides a comprehensive analysis of in-game auction data and introduces Sankey diagram visualizations for understanding player migration and behavior over time.

Findings

Player migration patterns identified

Churn rates analyzed over game lifetime

Visualization method aids in game economy management

Abstract

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.