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 (<a href="http://b.link/webshapes">http://b.link/webshapes</a>)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.
@inproceedings{shengmin2020webshapes,
title = {WebShapes: Network Visualization with 3D Shapes},
author = {Shengmin Jin and Richard Wituszynski and Max Caiello-Gingold and Reza Zafarani},
year = {2020},
keywords = {conference},
booktitle = {Proceedings of the 13th ACM International Conference on Web Search and Data Mining (WSDM)},
abstract = {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 (<a href="http://b.link/webshapes">http://b.link/webshapes</a>)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.},
pdf = {files/2020-WSDM-WebShapes.pdf},
}