TimeArcs: Visualizing Fluctuations in Dynamic Networks

T. N. Dang, N. Pendar, A. G. Forbes

Research output: Contribution to journalArticlepeer-review

40 Scopus citations


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.

Original languageEnglish
Pages (from-to)61-69
Number of pages9
JournalComputer Graphics Forum
Issue number3
StatePublished - Jun 1 2016


  • Categories and Subject Descriptors (according to ACM CCS):
  • H.5.2 [Information Interfaces and Presentation]: User Interfaces—Graphical user interfaces


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