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

Y. D. Cai, Channing Brown, Iftekhar Ahmed, Yannick Atouba Ada, Andrew Pilny, M. S. Poole
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引用次数: 3

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.
SocialMapExplorer:在时间地理空间中可视化大型多人在线游戏的社交网络
大型多人在线游戏(mmog)为调查大型社交网络提供了独特的机会,例如玩家(工作组)、交易和通信(聊天)网络。本文提出了一个可视化工具——SocialMapExplorer——允许用户在时间地理空间上探索这些网络。这个基于web的交互工具在GoogleMap框架上实现,应用视觉特征,包括颜色、大小、形状、粗细和字体,来表示各种网络特征。与其他类似工具不同的是,SocialMapExplorer将真实地图上的数据可视化,并将时间和空间信息与其他属性结合起来。为了应对密集计算的挑战,该工具在高性能计算机上运行。实现了三个模块:(1)NetViewer,通过在时间序列中可视化社交网络来分析网络动态;(2) GroupDetector,通过在可视化数据流中跟踪组来研究组的组装和进化;(3) CorrelationFinder,通过重叠普查数据和游戏日志数据的测量,研究选定的人口普查变量(如年龄、性别、种族、人口、收入、教育、职业和婚姻状况)和游戏玩法变量(如游戏时间、游戏频率、成就和损失)之间的相关性。我们对《EverQuestII》的游戏日志进行了研究。这个工具的演示展示了它如何帮助我们发现触发群体出现、缩小和扩大的事件,并探索人口普查数据和游戏数据之间的关系。本文介绍了该可视化工具的设计,演示了其在真实游戏数据上的功能,并讨论了其在时空空间关联的虚拟社交网络分析中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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