Webshapes: Network visualization with 3D shapes

S Jin, R Wituszynski, M Caiello-Gingold… - Proceedings of the 13th …, 2020 - dl.acm.org
S Jin, R Wituszynski, M Caiello-Gingold, R Zafarani
Proceedings of the 13th International Conference on Web Search and Data Mining, 2020dl.acm.org
Network visualization has played a critical role in graph analysis, as it not only presents a
big picture of a network but also helps reveal the structural information of a network. The
most popular visual representation of networks is the node-link diagram. However,
visualizing a large network with the node-link diagram can be challenging due to the
difficulty in obtaining an optimal graph layout. To address this challenge, a recent
advancement in network representation: network shape, allows one to compactly represent …
Network visualization has played a critical role in graph analysis, as it not only presents a big picture of a network but also helps reveal the structural information of a network. The most popular visual representation of networks is the node-link diagram. However, visualizing a large network with the node-link diagram can be challenging due to the difficulty in obtaining an optimal graph layout. To address this challenge, a recent advancement in network representation: network shape, allows one to compactly represent a network and its subgraphs with the distribution of their embeddings. Inspired by this research, we have designed a web platform WebShapes that enables researchers and practitioners to visualize their network data as customized 3D shapes (http://b.link/webshapes). Furthermore, we provide a case study on real-world networks to explore the sensitivity of network shapes to different graph sampling, embedding, and fitting methods, and we show examples of understanding networks through their network shapes.
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