TY - GEN
T1 - Discovering the influence of socioeconomic factors on online game behaviors
AU - Zhan, Min
AU - Cai, Y. Dora
AU - Guo, Dahai
N1 - Publisher Copyright:
© 2015 ACM.
PY - 2015/7/26
Y1 - 2015/7/26
N2 - With the rapid growth of popularity of online games in recent years, research has increased the knowledge about game playing behaviors and some demographic correlates, such as age and gender. Contributing to this line of research, we further examined the associations of socioeconomic factors (education, employment, income, and poverty status) and demographic characteristics (age, gender, and race/ethnicity) with online gaming behaviors (player count, total game sessions, total actions taken, and maximum level reached). We focused on one form of online games, Massively Multiplayer Online Games (MMOGs), which has received much attention recently. Analyses were conducted by extracting and linking the related data from the EverQuest II game logs, a popular form of MMOGs, and the summarized U.S. Census data for the zip-code areas of players from the state of Illinois (n=495). This study was performed on Gordon, a supercomputer hosted at San Diego Supercomputer center. Results from multiple regression analyses indicated positive associations between education rate (Bachelor's degree or above) and employment rate (for 16 years or older) at the zip-code level with game playing behaviors. The impact of median income on gaming behaviors appeared to operate through education and employment. Although male players outnumbered female players, female players tended to play more games sessions and take more actions. Results also indicated that a higher percentage of white population in a geography area seemed to be negatively related to game playing activities. These study findings provides valuable information and highlight the importance of further research and theoretical development in this area.
AB - With the rapid growth of popularity of online games in recent years, research has increased the knowledge about game playing behaviors and some demographic correlates, such as age and gender. Contributing to this line of research, we further examined the associations of socioeconomic factors (education, employment, income, and poverty status) and demographic characteristics (age, gender, and race/ethnicity) with online gaming behaviors (player count, total game sessions, total actions taken, and maximum level reached). We focused on one form of online games, Massively Multiplayer Online Games (MMOGs), which has received much attention recently. Analyses were conducted by extracting and linking the related data from the EverQuest II game logs, a popular form of MMOGs, and the summarized U.S. Census data for the zip-code areas of players from the state of Illinois (n=495). This study was performed on Gordon, a supercomputer hosted at San Diego Supercomputer center. Results from multiple regression analyses indicated positive associations between education rate (Bachelor's degree or above) and employment rate (for 16 years or older) at the zip-code level with game playing behaviors. The impact of median income on gaming behaviors appeared to operate through education and employment. Although male players outnumbered female players, female players tended to play more games sessions and take more actions. Results also indicated that a higher percentage of white population in a geography area seemed to be negatively related to game playing activities. These study findings provides valuable information and highlight the importance of further research and theoretical development in this area.
KW - Game behaviors
KW - MMOGs
KW - Online games
KW - Socioeconomic factors
UR - http://www.scopus.com/inward/record.url?scp=84942787167&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84942787167&partnerID=8YFLogxK
U2 - 10.1145/2792745.2792752
DO - 10.1145/2792745.2792752
M3 - Conference contribution
AN - SCOPUS:84942787167
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the XSEDE 2015 Conference
PB - Association for Computing Machinery
T2 - 4th Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2015
Y2 - 26 July 2015 through 30 July 2015
ER -