Community Fabric: Visualizing communities and structure in dynamic networks

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Information Visualization Pub Date : 2021-10-29 DOI:10.1177/14738716211056036
Evan Ezell, Seung-Hwan Lim, D. Anderson, R. Stewart
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引用次数: 0

Abstract

We present Community Fabric, a novel visualization technique for simultaneously visualizing communities and structure within dynamic networks. In dynamic networks, the structure of the network is continuously evolving throughout time and these underlying topological shifts tend to lead to communal changes. Community Fabric helps the viewer more easily interpret and understand the interplay of structural change and community evolution in dynamic graphs. To achieve this, we take a new approach, hybridizing two popular network and community visualizations. Community Fabric combines the likes of the Biofabric static network visualization method with traditional community alluvial flow diagrams to visualize communities in a dynamic network while also displaying the underlying network structure. Our approach improves upon existing state-of-the-art techniques in several key areas. We describe the methodologies of Community Fabric, implement the visualization using modern web-based tools, and apply our approach to three example data sets.
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社区结构:动态网络中可视化社区和结构
我们提出了CommunityFabric,这是一种新的可视化技术,用于同时可视化动态网络中的社区和结构。在动态网络中,网络的结构在整个时间内不断演变,这些潜在的拓扑变化往往会导致公共变化。CommunityFabric有助于观察者更容易地理解和理解动态图中结构变化和社区进化的相互作用。为了实现这一点,我们采取了一种新的方法,将两种流行的网络和社区可视化相结合。Community Fabric将Biofabric静态网络可视化方法与传统的社区冲积流图相结合,在动态网络中可视化社区,同时显示底层网络结构。我们的方法在几个关键领域改进了现有的最先进技术。我们描述了CommunityFabric的方法,使用现代基于web的工具实现可视化,并将我们的方法应用于三个示例数据集。
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来源期刊
Information Visualization
Information Visualization COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
5.40
自引率
0.00%
发文量
16
审稿时长
>12 weeks
期刊介绍: Information Visualization is essential reading for researchers and practitioners of information visualization and is of interest to computer scientists and data analysts working on related specialisms. This journal is an international, peer-reviewed journal publishing articles on fundamental research and applications of information visualization. The journal acts as a dedicated forum for the theories, methodologies, techniques and evaluations of information visualization and its applications. The journal is a core vehicle for developing a generic research agenda for the field by identifying and developing the unique and significant aspects of information visualization. Emphasis is placed on interdisciplinary material and on the close connection between theory and practice. This journal is a member of the Committee on Publication Ethics (COPE).
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