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PeckVis: A Visual Analytics Tool to Analyze Dominance Hierarchies in Small Groups.
IEEE Transactions on Visualization and Computer Graphics ( IF 5.2 ) Pub Date : 2020-02-05 , DOI: 10.1109/tvcg.2020.2969056
Darius Coelho , Ivan Chase , Klaus Mueller

The formation of social groups is defined by the interactions among the group members. Studying this group formation process can be useful in understanding the status of members, decision-making behaviors, spread of knowledge and diseases, and much more. A defining characteristic of these groups is the pecking order or hierarchy the members form which help groups work towards their goals. One area of social science deals with understanding the formation and maintenance of these hierarchies, and in our work we provide social scientists with a visual analytics tool - PeckVis - to aid this process. While online social groups or social networks have been studied deeply and lead to a variety of analyses and visualization tools, the study of smaller groups in the field of social science lacks the support of suitable tools. Domain experts believe that visualizing their data can save them time as well as reveal findings they may have failed to observe. We worked alongside domain experts to build an interactive visual analytics system to investigate social hierarchies. Our system can discover patterns and relationships between the members of a group as well as compare different groups. The results are presented to the user in the form of an interactive visual analytics dashboard. We demonstrate that domain experts were able to effectively use our tool to analyze animal behavior data.

中文翻译:

PeckVis:一种可视化分析工具,用于分析小组中的支配地位层次结构。

社会群体的形成是由群体成员之间的相互作用来定义的。研究此小组形成过程可有助于理解成员的状态,决策行为,知识和疾病的传播等。这些小组的定义特征是成员形成的啄食顺序或等级,以帮助小组朝着自己的目标努力。社会科学的一个领域涉及了解这些层次结构的形成和维护,在我们的工作中,我们为社会科学家提供了一种视觉分析工具PeckVis,以协助这一过程。尽管对在线社交团体或社交网络进行了深入研究并导致了各种分析和可视化工具,但社会科学领域中较小团体的研究却缺乏合适工具的支持。领域专家认为,可视化其数据可以节省时间,并揭示他们可能未观察到的发现。我们与领域专家合作,构建了一个交互式的视觉分析系统来调查社会层次结构。我们的系统可以发现组成员之间的模式和关系,也可以比较不同的组。结果以交互式视觉分析仪表板的形式呈现给用户。我们证明了领域专家能够有效地使用我们的工具来分析动物行为数据。我们的系统可以发现组成员之间的模式和关系,也可以比较不同的组。结果以交互式视觉分析仪表板的形式呈现给用户。我们证明了领域专家能够有效地使用我们的工具来分析动物行为数据。我们的系统可以发现组成员之间的模式和关系,也可以比较不同的组。结果以交互式视觉分析仪表板的形式呈现给用户。我们证明了领域专家能够有效地使用我们的工具来分析动物行为数据。
更新日期:2020-02-28
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