Identifying a Typology of Players Based on Longitudinal Game Data

Iftekhar Ahmed, Amogh Mahapatra, Marshall Scott Poole, Jaideep Srivastava, Channing Brown

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Citations (Scopus)


This study describes an approach to identify a typology of players based on longitudinal game data. The study explored anonymous user log data of 1854 players of EverQuest II (EQII)—a massively multiplayer online game (MMOG). The study tracked ten specific in-game player behavior including types of activities, activity related rewards, and casualties for 27 weeks. The objective of the study was to understand player characteristics and behavior from longitudinal data. Primary analysis revealed meaningful typologies, differences among players based on identified typologies, and differences between individual and group related gaming situations.

Original languageEnglish
Title of host publicationSpringer Proceedings in Complexity
Number of pages13
VolumePart F3
Publication statusPublished - 1 Jan 2014
Externally publishedYes



  • Game typology
  • MMOs
  • Player typology

ASJC Scopus subject areas

  • Applied Mathematics
  • Modelling and Simulation
  • Computer Science Applications

Cite this

Ahmed, I., Mahapatra, A., Poole, M. S., Srivastava, J., & Brown, C. (2014). Identifying a Typology of Players Based on Longitudinal Game Data. In Springer Proceedings in Complexity (Vol. Part F3, pp. 103-115). Springer.