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Entropy Based Sensitivity Analysis and Visualization of Social Networks

机译:基于熵的敏感性分析与社交网络可视化

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This paper introduces a technique to analyze and visualize social networks using Shannon's entropy model. Entropy is exploited to measure the information amount in social network graphs, and to conduct sensitivity analyses. Novel measures such as degree, betweenness and closeness entropies are evaluated to find the change in graph entropy or the actors. In this work we present a visualization approach that uses coloring, sizing and filtering to help the users perceive the communicated information. The result of sensitivity analyses is integrated into the visualization using the change amount caused by the actors as information. The main contribution of this study is a visualization where the information communicated from a social network is enhanced by the help of sensitivity analyses.
机译:本文介绍了一种使用Shannon熵模型分析和可视化社交网络的技术。 利用熵来衡量社交网络图中的信息量,并进行敏感性分析。 评估诸如程度,之间的新措施,以获得图形熵或演员的变化。 在这项工作中,我们提出了一种可视化方法,它使用着色,大小化和过滤来帮助用户感知传达的信息。 敏感性分析的结果使用由演员作为信息引起的变化量集成到可视化中。 本研究的主要贡献是一种可视化,其中通过敏感性分析来增强来自社交网络的信息。

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