Eiffel: Evolutionary Flow Map for Influence Graph Visualization

Yucheng Huang, Lei Shi, Yue Su, Yifan Hu, Hanghang Tong, Chaoli Wang, Tong Yang, Deyun Wang, Shuo Liang

Research output: Contribution to journalArticlepeer-review


The visualization of evolutionary influence graphs is important for performing many real-life tasks such as citation analysis and social influence analysis. The main challenges include how to summarize large-scale, complex, and time-evolving influence graphs, and how to design effective visual metaphors and dynamic representation methods to illustrate influence patterns over time. In this work, we present Eiffel, an integrated visual analytics system that applies triple summarizations on evolutionary influence graphs in the nodal, relational, and temporal dimensions. In numerical experiments, Eiffel summarization results outperformed those of traditional clustering algorithms with respect to the influence-flow-based objective. Moreover, a flow map representation is proposed and adapted to the case of influence graph summarization, which supports two modes of evolutionary visualization (i.e., flip-book and movie) to expedite the analysis of influence graph dynamics. We conducted two controlled user experiments to evaluate our technique on influence graph summarization and visualization respectively. We also showcased the system in the evolutionary influence analysis of two typical scenarios, the citation influence of scientific papers and the social influence of emerging online events. The evaluation results demonstrate the value of Eiffel in the visual analysis of evolutionary influence graphs.

Original languageEnglish (US)
Article number8673661
Pages (from-to)2944-2960
Number of pages17
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number10
StatePublished - Oct 1 2020
Externally publishedYes


  • Influence graph
  • citation analysis
  • dynamic visualization

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design


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