WebShapes: Network Visualization with 3D Shapes

Shengmin Jin, Richard Wituszynski, Max Caiello-Gingold, R. Zafarani
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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 (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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WebShapes:具有3D形状的网络可视化
网络可视化在图分析中起着至关重要的作用,因为它不仅能呈现网络的全貌,而且有助于揭示网络的结构信息。最流行的网络可视化表示是节点链接图。然而,由于难以获得最佳的图布局,使用节点链接图可视化大型网络可能具有挑战性。为了应对这一挑战,网络表示的最新进展:网络形状,允许人们用嵌入的分布紧凑地表示网络及其子图。受到这项研究的启发,我们设计了一个网络平台WebShapes,使研究人员和从业者能够将他们的网络数据可视化为定制的3D形状(http://b.link/webshapes)。此外,我们提供了一个现实世界网络的案例研究,以探索网络形状对不同图采样、嵌入和拟合方法的敏感性,并展示了通过网络形状理解网络的示例。
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