• DocumentCode
    1824854
  • Title

    ChurnVis: Visualizing mobile telecommunications churn on a social network with attributes

  • Author

    Archambault, Daniel ; Hurley, Neil ; Cuong To Tu

  • Author_Institution
    Clique Strategic Res. Cluster, Univ. Coll. Dublin, Dublin, Ireland
  • fYear
    2013
  • fDate
    25-28 Aug. 2013
  • Firstpage
    894
  • Lastpage
    901
  • Abstract
    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.
  • Keywords
    data privacy; data visualisation; mobile communication; mobile computing; social networking (online); ChurnVis; churn components; components visualization; data analysis; data presentation tasks; data privacy constraints; dynamic attributes; mobile telecommunications churn visualization; service provider; social influence; social network; static attributes; subscriber actions; Companies; Data visualization; Histograms; Mobile communication; Mobile computing; Social network services; Telecommunications; Attributed Graphs; Social Networks; Telecommunications Churn; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Social Networks Analysis and Mining (ASONAM), 2013 IEEE/ACM International Conference on
  • Conference_Location
    Niagara Falls, ON
  • Type

    conf

  • Filename
    6785806