A large-scale, longitudinal study of user profiles in world of warcraft

  • Authors:

  • Jonathan Bell;Swapneel Sheth;Gail Kaiser

  • Affiliations:

  • Columbia University, New York, NY, USA;Columbia University, New York, NY, USA;Columbia University, New York, NY, USA

  • Venue:
  • Proceedings of the 22nd international conference on World Wide Web companion
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

We present a survey of usage of the popular Massively Multiplayer Online Role Playing Game, World of Warcraft. Players within this game often self-organize into communities with similar interests and/or styles of play. By mining publicly available data, we collected a dataset consisting of the complete player history for approximately six million characters, with partial data for another six million characters. The paper provides a thorough description of the distributed approach used to collect this massive community data set, and then focuses on an analysis of player achievement data in particular, exposing trends in play from this highly successful game. From this data, we present several findings regarding player profiles. We correlate achievements with motivations based upon a previously-defined motivation model, and then classify players based on the categories of achievements that they pursued. Experiments show players who fall within each of these buckets can play differently, and that as players progress through game content, their play style evolves as well.