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Aging Agents: Cross Generational Analysis of Behavior and Need Satisfaction Among Players of Tom Clancy’s The Division 2
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Ubisoft Massive, Consumer Experience, User Research. (DDS)ORCID iD: 0000-0002-6016-028X
2020 (English)In: The Computer Games Journal, ISSN 2052-773X, Vol. 9, p. 245-262Article in journal (Refereed) Published
Abstract [en]

This research investigated the effect of age on players of an online multiplayer shooter. Through combining the data from two large scale surveys, we collected information regarding age, gaming habits, game rating and psychological need satisfaction for 8120 players of Tom Clancy’s The Division. Behavioral data extracted from the game’s tracking engine was then cross-referenced for different age groups to indicate motivational, behavioral and habitual characteristics of each age group. To find the importance of measured factors we employed a rank-based model for comparing independent sample means for intergenerational analysis (Kendall’s tau for non-parametric correlations) as well as multiple Machine Learning algorithms. Results found that different measures of playtime vary significantly among generations. Baby Boomers showed significantly higher playtime, days played and group playtime. Intergenerational comparison of perceived need satisfaction also found that older gamers feel more agentic, present in the narrative, closer to non-playable characters but less competent at the game. Percentage of group playtime also showed a decrease in older generations. Future research may expand cross generational analysis to other game types and include more granular behavioral measures.

Place, publisher, year, edition, pages
Springer, 2020. Vol. 9, p. 245-262
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:mau:diva-17329DOI: 10.1007/s40869-020-00104-6OAI: oai:DiVA.org:mau-17329DiVA, id: diva2:1431006
Available from: 2020-05-18 Created: 2020-05-18 Last updated: 2021-03-25Bibliographically approved
In thesis
1. Predictive Psychological Player Profiling
Open this publication in new window or tab >>Predictive Psychological Player Profiling
2021 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Video games have become the largest portion of the entertainment industry and everyday life of millions of players around the world. Considering games as cultural artifacts, it seems imperative to study both games and players to understand underlying psychological and behavioral implications of interacting with this medium, especially since video games are rich domains for occurrence of rich affective experiences annotated by and measurable via in-game behavior. This thesis is a presentation of a series of studies that attempt to model player perception and behavior as well as their psychosocial attributes in order to make sense of interrelations of these factors and implications the findings have for game designers and researchers. In separate studies including survey and in-game telemetry data of millions of players, we delve into reliable measures of player psychological need satisfaction, motivation and generational cohort and cross reference them with in-game behavioral patterns by presenting systemic frameworks for classification and regression. We introduce a measurement of perceived need satisfaction and discuss generational effects in playtime and motivation, present a robust prediction model for ordinally processed motivations and review classification techniques when it comes to playstyles derived from player choices. Additionally, social aspects of play, such as social influence and contagion as well as disruptive behavior, is discussed along with advanced statistical models to detect and explain them.   

Place, publisher, year, edition, pages
Malmö: Malmö universitet, 2021. p. 121
Series
Studies in Computer Science
Keywords
Human-Computer Interaction, Affective Computing, Player Experience, User Research, Behavioral modeling, Psychology of play
National Category
Human Computer Interaction
Identifiers
urn:nbn:se:mau:diva-41436 (URN)
Presentation
2021-05-27, Zoom, 17:00 (English)
Supervisors
Note

Vid tidpunkten för disputationen var följande delarbete opublicerat: delarbete I (manuskript).

At the time of the doctoral defence the following paper was unpublished: paper I (manuscript).

Available from: 2021-03-26 Created: 2021-03-25 Last updated: 2022-10-17Bibliographically approved

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Azadvar, Ahmad

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