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The Use of Social Science Methods to Predict Player Characteristics from Avatar Observations

  • Carl SymborskiEmail author
  • Gary M. Jackson
  • Meg Barton
  • Geoffrey Cranmer
  • Byron Raines
  • Mary Magee Quinn
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

The purpose of this study was to investigate the extent to which real world characteristics of massively multiplayer online role-playing game (MMORPG) players can be predicted based on the characteristics and behavior of their avatars. Ground truth on participants’ real world characteristics was obtained through the administration of validated measures of personality and authoritarian ideology, as well as a demographics form. A team of trained assessors used quantitative assessment instruments to evaluate avatar characteristics, behavior, and personality from a recorded session of the participant’s typical gameplay. The statistical technique of discriminant analysis was then applied to create predictive models for players’ real world characteristics such as gender, approximate age, and education level, using the variables generated through observational assessment of the avatar.

Keywords

Social sciences Behavioral studies Avatars Online games MMORPGs Virtual worlds 

Notes

Acknowledgments

We express our thanks to Dr. Celia Pearce, Kathleen Wipf, Jasmine Pettiford, Nic Watson, Hank Whitson, and Patrick Coursey for their work and contributions on this project.

* Reproduced by special permission of the Publisher, Psychological Assessment Resources, Inc., 16204 North Florida Avenue, Lutz, Florida 33549, from the NEO Personality Inventory-Revised by Paul T. Costa Jr., PhD and Robert R. McCrae, PhD, Copyright 1978, 1985, 1989, 1991, 1992 by Psychological Assessment Resources, Inc. (PAR). Further reproduction is prohibited without permission of PAR.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Carl Symborski
    • 1
    Email author
  • Gary M. Jackson
    • 1
  • Meg Barton
    • 1
  • Geoffrey Cranmer
    • 1
  • Byron Raines
    • 1
  • Mary Magee Quinn
    • 1
  1. 1.LeidosArlingtonUSA

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