M. Waldner, D. Steinböck, E. Gröller:
"Interactive exploration of large time-dependent bipartite graphs";
Journal of Computer Languages, 57 (2020), 2; S. 1 - 16.

Kurzfassung englisch:
Bipartite graphs are typically visualized using linked lists or matrices, but these visualizations neither scale well nor do they convey temporal development. We present a new interactive exploration interface for large, time-dependent bipartite graphs. We use two clustering techniques to build a hierarchical aggregation supporting different exploration strategies. Aggregated nodes and edges are visualized as linked lists with nested time series. We demonstrate two use cases: finding advertising expenses of public authorities following similar temporal patterns and comparing author-keyword co-occurrences across time. Through a user study, we show that linked lists with hierarchical aggregation lead to more insights than without.

Information visualization, Bipartite graphs, Clustering, Time series data, Insight-based evaluation

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