ChurnVis:可视化带有属性的社交网络上的移动通信流失

D. Archambault, N. Hurley, Cuong To Tu
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引用次数: 7

摘要

在本文中,我们提出了ChurnVis,一个可视化组件的系统,受移动电信流失和用户的行动随时间的影响。我们描述了我们在一家网络分析公司中部署该系统的经验,该系统用于数据分析和表示任务。由于社会影响似乎是移动通信流失(用户决定离开特定服务提供商)的一个因素,因此可视化是基于从用户之间的呼叫数据推断出的社会网络。使用这个网络,流失者组成部分或在社交网络中连接的流失者群体被分割出来,其静态和动态属性的趋势被可视化。ChurnVis帮助分析人员以一种尊重服务提供商的数据隐私约束的方式了解这些组件的趋势。通过这两种管道方法,我们能够从数以亿计的边缘的社交网络中过滤出成千上万的流失成分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ChurnVis: Visualizing mobile telecommunications churn on a social network with attributes
In this paper, we present ChurnVis, a system for visualizing components affected by mobile telecommunications churn and subscriber actions over time. We describe our experience of deploying this system in a network analytics company for use in data analysis and presentation tasks. As social influence seems to be a factor in mobile telecommunications churn (the decision of a subscriber to leave a particular service provider), the visualization is based on a social network inferred from calling data between subscribers. Using this network, churn components, or groups of churners who are connected in the social network, are segmented out and trends in their static and dynamic attributes are visualized. ChurnVis helps analysts understand trends in these components in a way that respects the data privacy constraints of the service provider. Through this two pipeline approach, we are able to visualize thousands of churn components filtered from a social network of hundreds of millions of edges.
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