Visual Matrix Clustering of Social Networks

Wong; Pak Chung; Mackey; Patrick; Foote; Harlan; May; Richard

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Visual Matrix Clustering of Social Networks

机译：社交网络的视觉矩阵聚类

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摘要

The prevailing choices to graphically represent a social network are a node-link graph and an adjacency matrix. Both techniques have unique strengths and weaknesses for different domain applications. This article focuses on how to change adjacency matrices from merely showing pairwise associations among network actors (or graph nodes) to depicting clusters of a social network. Node-link graphs supplement the discussion.

机译：以图形方式表示社交网络的主要选择是节点链接图和邻接矩阵。两种技术对于不同的领域应用都有独特的优点和缺点。本文重点介绍如何更改邻接矩阵，从仅显示网络参与者（或图形节点）之间的成对关联到描述社交网络的群集。节点链接图补充了讨论。

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来源
《IEEE Computer Graphics and Applications》 |2013年第4期|88-96|共9页
作者
Wong; Pak Chung; Mackey; Patrick; Foote; Harlan; May; Richard;
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作者单位

Pacific Northwest National Laboratory|c|;

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原文格式 PDF
正文语种 eng
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关键词
adjacency matrix; computer graphics; node-link graph; social networks; visual analytics; visualization;

机译：邻接矩阵;计算机图形学;节点链接图;社交网络;视觉分析;可视化;

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机译：时间矩阵：使用基于交互式矩阵的可视化分析时间性社交网络
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机译：基于K-Nodes更新策略和相似性矩阵的多目标聚类技术在社交网络中挖掘社区
3. Visual hierarchical cluster structure: A refined co-association matrix based visual assessment of cluster tendency [J] . Zhong Caiming, Yue Xiaodong, Lei Jingsheng Pattern recognition letters . 2015,第jula1期

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4. Enhancing Interdisciplinary Cooperation by Social Platforms Assessing the Usefulness of Bibliometric Social Network Visualization in Large-Scale Research Clusters [C] . Andre Calero Valdez, Anne Kathrin Schaar, Martina Ziefle, International conference on human-computer interaction . 2014

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5. Data clustering and visualization through matrix factorization. [D] . Chen, Yanhua. 2010

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6. Representing Degree Distributions Clustering and Homophily in Social Networks With Latent Cluster Random Effects Models [O] . Pavel N. Krivitsky, Mark S. Handcock, Adrian E. Raftery, -1

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机译：MatLink：用于分析社交网络的增强矩阵可视化

Visual Matrix Clustering of Social Networks

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