Identifying a Typology of Players Based on Longitudinal Game Data

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

doi:10.1007/978-3-319-07142-8_7

Identifying a Typology of Players Based on Longitudinal Game Data

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

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter

4 Scopus citations

Abstract

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 language	English (US)
Title of host publication	Springer Proceedings in Complexity
Publisher	Springer
Pages	103-115
Number of pages	13
DOIs	https://doi.org/10.1007/978-3-319-07142-8_7
State	Published - 2014

Publication series

Name	Springer Proceedings in Complexity
ISSN (Print)	2213-8684
ISSN (Electronic)	2213-8692

Bibliographical note

Funding Information:
This research was supported by the National Science Foundation (NSF IIS-0729421), the Army Research Institute (ARI W91WAW-08-C-0106), Air Force Research Lab (AFRL Contract No. FA8650-10-C-7010), the Army Research Lab (ARL) Network Science— Collaborative Technology Alliance (NS-CTA) via BBN TECH/W911NF-09-2-0053, and the National Science Foundation via the XSEDE project’s Extended Collaborative Support Service under Grant # NSF-OCI 1053575. The data used for this research was provided by the SONY Online Entertainment. The findings represent solely the opinions of the authors and not of the sponsors.

Funding Information:
Acknowledgments This research was supported by the National Science Foundation (NSF IIS-0729421), the Army Research Institute (ARI W91WAW-08-C-0106), Air Force Research Lab (AFRL Contract No. FA8650-10-C-7010), the Army Research Lab (ARL) Network Science— Collaborative Technology Alliance (NS-CTA) via BBN TECH/W911NF-09-2-0053, and the National Science Foundation via the XSEDE project’s Extended Collaborative Support Service under Grant # NSF-OCI 1053575. The data used for this research was provided by the SONY Online Entertainment. The findings represent solely the opinions of the authors and not of the sponsors.

Publisher Copyright:
© 2014, Springer International Publishing Switzerland.

Keywords

Game typology
MMORPGs
MMOs
Player typology

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10.1007/978-3-319-07142-8_7

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abstract = "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.",

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note = "Funding Information: This research was supported by the National Science Foundation (NSF IIS-0729421), the Army Research Institute (ARI W91WAW-08-C-0106), Air Force Research Lab (AFRL Contract No. FA8650-10-C-7010), the Army Research Lab (ARL) Network Science— Collaborative Technology Alliance (NS-CTA) via BBN TECH/W911NF-09-2-0053, and the National Science Foundation via the XSEDE project{\textquoteright}s Extended Collaborative Support Service under Grant # NSF-OCI 1053575. The data used for this research was provided by the SONY Online Entertainment. The findings represent solely the opinions of the authors and not of the sponsors. Funding Information: Acknowledgments This research was supported by the National Science Foundation (NSF IIS-0729421), the Army Research Institute (ARI W91WAW-08-C-0106), Air Force Research Lab (AFRL Contract No. FA8650-10-C-7010), the Army Research Lab (ARL) Network Science— Collaborative Technology Alliance (NS-CTA) via BBN TECH/W911NF-09-2-0053, and the National Science Foundation via the XSEDE project{\textquoteright}s Extended Collaborative Support Service under Grant # NSF-OCI 1053575. The data used for this research was provided by the SONY Online Entertainment. The findings represent solely the opinions of the authors and not of the sponsors. Publisher Copyright: {\textcopyright} 2014, Springer International Publishing Switzerland.",

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Identifying a Typology of Players Based on Longitudinal Game Data

Abstract

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