球体图与图形的社会网络可视化

Mithileysh Sathiyanarayanan, Donato Pirozzi
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引用次数: 14

摘要

随着社会网络信息的不断增长,总是需要更好的信息可视化技术来进行各种各样的分析,这通常被称为社会网络分析。社交网络已经成为一个巨大的广告平台,在那里,公司瞄准的是高度联系的用户,而不是更孤立的用户。为了瞄准高度连接的用户和他们的活动,各种研究人员测试了可视化效果,如欧拉图、树图、图形及其组合。尽管欧拉图与图以及树图与图的结合提供了一些有趣的结果,但还有一个问题有待回答,那就是可扩展性。在本文中,我们提出了一种新的可视化技术,“带图的球体图”,它解决了可扩展性问题。然后,将该新技术与传统的欧拉图进行了比较,并使用twitter案例进行了实证研究。28名参与者被暴露在一个软件中的18个图表(每种可视化类型的9个图表)中,该软件记录了准确性和反应时间(即性能测量)。504次观测结果表明:(a)两种可视化结果在准确率上无显著差异,(b)两种可视化结果在响应时间上有显著差异。此外,用户被要求在两种可视化(即偏好度量)之间进行扩展,其中75%的用户更喜欢带有图形的Spherule图,因为它的简单性、全面性、导航、对齐(布局)、集合排序和数据项排序特征。我们的结论是,带有图形的球体图将有利于信息可视化社区中正在探索商业社交网络的研究人员和实践者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spherule diagrams with graph for social network visualization
As social network information keeps growing, there is always a need for better information visualization techniques for carrying out multifarious analysis, which is commonly called as social network analysis. Social networks have become a big platform for advertisements, where a company targets highly connected than to more isolated users. To target highly connected users and their activities, visualizations such as Euler diagrams, Treemap diagrams, graphs and their combinations were tested by various researchers. Though Euler diagrams combined with graph and Treemap diagrams with graph have provided some interesting results, the one question yet to be answered is the scalability. In this paper, we propose a novel visual technique, “Spherule diagrams with graph”, which addresses the scalability issue. The novel technique is then compared with the traditional Euler diagrams with graph using a twitter case study in an empirical form. Twenty-eight participants were exposed to eighteen diagrams (nine diagrams of each type of visualization) in a software which recorded accuracy and response time (i.e., performance measure). The results of 504 observations indicate that (a) there is no significant difference between the visualizations in terms of accuracy and (b) there is a significant difference between the visualizations in terms of response time. Also, users were asked to aggrandize between the two visualizations (i.e., preference measure), where 75% preferred Spherule diagrams with graph for its simplicity, comprehensiveness, navigation, alignment (layout), set ordering and data items ordering characteristics. We conclude that, Spherule diagrams with graph will be beneficial for researchers and practitioners in the information visualization community who are exploring social networks for business.
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