State-based network similarity visualization

Murugesan, Sugeerth; Bouchard, Kristofer; Brown, Jesse; Kiran, Mariam; Lurie, Dan; Hamann, Bernd; Weber, Gunther H

doi:10.1177/1473871619882019

State-based network similarity visualization

Journal Article · Mon Nov 04 00:00:00 EST 2019 · Information Visualization

DOI:https://doi.org/10.1177/1473871619882019· OSTI ID:1581082

^[1]; Bouchard, Kristofer ^[2]; Brown, Jesse ^[3]; Kiran, Mariam ^[2]; Lurie, Dan ^[4]; Hamann, Bernd ^[5]; Weber, Gunther H ^[1]

Univ. of California, Davis, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Univ. of California, San Francisco, CA (United States)
Univ. of California, Berkeley, CA (United States)
Univ. of California, Davis, CA (United States)

We introduce an approach for the interactive visual analysis of weighted, dynamic networks. These networks arise in areas such as computational neuroscience, sociology, and biology. Network analysis remains challenging due to complex time-varying network behavior. For example, edges disappear/reappear, communities grow/vanish, or overall network topology changes. Our technique, TimeSum, detects the important topological changes in graph data to abstract the dynamic network and visualize one summary representation for each temporal phase, a state. We define a network state as a graph with similar topology over a specific time interval. To enable a holistic comparison of networks, we use a difference network to depict edge and community changes. Here, we present case studies to demonstrate that our methods are effective and useful for extracting and exploring complex dynamic behavior of networks.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1581082

Journal Information:: Information Visualization, Journal Name: Information Visualization Journal Issue: 2 Vol. 19; ISSN 1473-8716

Publisher:: SAGECopyright Statement

Country of Publication:: United States

Language:: English

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