SocialMapExplorer: visualizing social networks of massively multiplayer online games in temporal-geographic space

Authors:
Y. Dora Cai;Channing Brown;Iftekhar Ahmed;Yannick Atouba;Andrew Pilny;Marshall Scott Poole
Affiliations:
Univ. of Illinois, Urbana, IL;Univ. of Illinois, Urbana, IL;Univ. of North Texas, Denton, TX;University of Illinois, Urbana, IL;University of Illinois, Urbana, IL;University of Illinois, Urbana, IL
Venue:
Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery
Year:
2013

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Abstract

Massively Multiplayer Online Games (MMOGs) provide unique opportunities to investigate large social networks, such as player (working-group), trading, and communication (chat) networks. This paper presents a visualization tool -- SocialMapExplorer - that allows users to explore these networks over temporal-geographic space. Implemented on the GoogleMap framework, this web-based interactive tool applies visual features, including color, size, shape, weight and font, to represent various network features. Unlike other similar tools, SocialMapExplorer visualizes data on a real map and couples time and spatial information with other attributes. To meet the challenge of intensive computation, this tool runs on high performance computers. Three modules have been implemented: (1) NetViewer that analyzes network dynamics by visualizing social networks in time series; (2) GroupDetector that investigates group assembly and evolution by tracing groups in visualized data flow; and (3) CorrelationFinder that studies the correlation between selected census variables (such as age, gender, race, population, income, education, occupation, and marital status) and game-play variables (such as play time, play frequency, achievement, and loss) by overlapping the measurements of census data and game log data. We performed this study on EverQuestII (EQII) game logs. This demonstration of the tool shows how it can help us discover events that trigger a group to emerge, shrink, and expand, and explore the relationship between census data and game data. This paper presents the design of this visualization tool, demonstrates its functions on real game data, and discusses its applications to virtual social network analysis associated with temporal-geographic space.