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TimeMatrix: Analyzing Temporal Social Networks Using Interactive Matrix-Based Visualizations

机译:时间矩阵:使用基于交互式矩阵的可视化分析时间性社交网络

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摘要

Visualization plays a crucial role in understanding dynamic social networks at many different levels (i.e., group, subgroup, and individual). Node-link-based visualization techniques are currently widely used for these tasks and have been demonstrated to be effective, but it was found that they also have limitations in representing temporal changes, particularly at the individual and subgroup levels. To overcome these limitations, this article presents a new network visualization technique, called "TimeMatrix," based on a matrix representation. Interaction techniques, such as overlay controls, a temporal range slider, semantic zooming, and integrated network statistical measures, support analysts in studying temporal social networks. To validate the design, the article presents a user study involving three social scientists analyzing inter-organizational collaboration data. The study demonstrates how TimeMatrix may help analysts gain insights about the temporal aspects of network data that can be subsequently tested with network analytic methods.
机译:可视化在理解许多不同级别(即小组,子小组和个人)的动态社交网络中起着至关重要的作用。基于节点链接的可视化技术目前已广泛用于这些任务,并已被证明是有效的,但是发现它们在表示时间变化方面也存在局限性,特别是在个人和子组级别。为了克服这些限制,本文提出了一种基于矩阵表示的新的网络可视化技术,称为“ TimeMatrix”。交互技术(如覆盖控件,时间范围滑块,语义缩放和集成的网络统计量度)为分析人员研究时间社交网络提供了支持。为了验证设计,本文提出了一项用户研究,其中涉及三名社会科学家,他们分析了组织间的协作数据。这项研究证明了TimeMatrix如何帮助分析师获得有关网络数据的时态方面的见解,这些见解随后可以使用网络分析方法进行测试。

著录项

  • 来源
    《International journal of human-computer interaction》 |2010年第12期|p.1031-1051|共21页
  • 作者单位

    School of Industrial Engineering,Purdue University, West Lafayette, Indiana 315 North Grant Street, West Lafayette, IN 47907;

    School of Electrical and Computer Engineering,Purdue University, West Lafayette, Indiana;

    Department of Communication,Purdue University, West Lafayette, Indiana;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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