Visualization of trends in subscriber attributes of communities on mobile telecommunications networks
|Title:||Visualization of trends in subscriber attributes of communities on mobile telecommunications networks||Authors:||Archambault, Daniel
Hurley, Neil J.
|Permanent link:||http://hdl.handle.net/10197/8369||Date:||Dec-2014||Abstract:||Churn, the decision for a subscriber to leave a provider, is frequently of interest in the telecommunications industry. Previous research provides evidence that social influence can be a factor in mobile telecommunications churn. In our work, presented at ASONAM, we presented a system, called ChurnVis, to visualize the evolution of mobile telecommunications churn and subscriber actions over time. First, we infer a social network from call detail records. Then, we compute components based on an overlay of this social network and churn activity. We compute summaries of the attributes associated with the subscribers and finally, we visualize the components in a privacy preserving way. The system is able to present summaries of thousands of churn components in graphs of hundreds of millions of edges. One of the drawbacks of the original approach was that churn components were sometimes very large, leading to over-aggregation in the summary data. In this extension of the ASONAM paper, we adapt the ChurnVis approach to operate on the output of a community finding algorithm and present new results based on this adaptation.||Funding Details:||Science Foundation Ireland||Type of material:||Journal Article||Publisher:||Springer||Keywords:||Machine learning;Statistics;Telecommunications churn;Attributed graphs;Graph visualization;Social networks;Community finding visualization||DOI:||10.1007/s13278-014-0205-5||Language:||en||Status of Item:||Peer reviewed|
|Appears in Collections:||Computer Science Research Collection|
Insight Research Collection
Show full item record