@article{PB-VRVis-2020-058,
author = {Waldner, Manuela and Steinb{\"o}ck, Daniel and Gr{\"o}ller, Eduard},
title = {Interactive exploration of large time-dependent bipartite graphs},
year = {2020},
journaltitle = {Journal of Computer Languages},
doi = {https://doi.org/10.1016/j.cola.2020.100959},
url = {https://www.vrvis.at/publications/PB-VRVis-2020-058},
volume = {57},
abstract = {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.},
keywords = {Information visualization; Bipartite graphs; Clustering; Time series data; Insight-based evaluation},
month = {April 2020},
}