TimeArcs: Visualizing Fluctuations in Dynamic Networks
TimeArcs: Visualizing Fluctuations in Dynamic Networks
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DOI：
10.1111/cgf.12882
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发表时间：
2016-06
影响因子：
2.5
通讯作者：
Tuan Nhon Dang;Nick Pendar;A. Forbes
中科院分区：
文献类型：
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作者：
Tuan Nhon Dang;Nick Pendar;A. Forbes
在本文中，我们介绍TimeArcs，一种新的可视化技术，用于表示网络中实体之间的动态关系。力导向布局提供了一种通过将相关实体彼此靠近来突出显示它们的方法。通过施加在节点上的力和节点之间的连接，实体彼此靠近（形成集群）。在许多应用领域中，实体之间的关系在时间上并不稳定，这意味着集群结构和集群成员也可能随时间而变化。我们的方法将不同时间点的多个力导向布局合并为一个全面的可视化，在用户定义的时间段内提供最重要集群的大图概述。TimeArcs还支持一系列交互式功能，例如允许用户向下钻取以查看有关特定集群的详细信息。为了突出这种技术的好处，我们展示了它在各种数据集上的应用，包括IMDB co-星星网络，一个显示蛋白质相互作用的生物医学文献中相互矛盾的证据的数据集，以及从政治博客中获得的搭配流行短语。
In this paper we introduce TimeArcs, a novel visualization technique for representing dynamic relationships between entities in a network. Force‐directed layouts provide a way to highlight related entities by positioning them near to each other Entities are brought closer to each other (forming clusters) by forces applied on nodes and connections between nodes. In many application domains, relationships between entities are not temporally stable, which means that cluster structures and cluster memberships also may vary across time. Our approach merges multiple force‐directed layouts at different time points into a single comprehensive visualization that provides a big picture overview of the most significant clusters within a user‐defined period of time. TimeArcs also supports a range of interactive features, such as allowing users to drill‐down in order to see details about a particular cluster. To highlight the benefits of this technique, we demonstrate its application to various datasets, including the IMDB co‐star network, a dataset showing conflicting evidences within biomedical literature of protein interactions, and collocated popular phrases obtained from political blogs.