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Large-Scale Social Network Analysis Software Services for the Telecommunications Industry

Dimension Value
  • Discipline
  • Structural Sciences
    • Mathematics
  • Project Working Hours
  • Not Specified
  • Research Study Hybrid Value Creation
  • Not Specified
  • Funding Institutions
  • National governmental Funding
    • Other
  • Other Funding Institutions
  • National Science Foundation
Contact Person/s: Dr. Nathan Eagle

Large-Scale Social Network Analysis Software Services for the Telecommunications Industry (SBIR)

This Small Business Innovation Research Phase I project will investigate the potential of using call log data to assist the telecommunications industry in better serving its customers. Call logs (records of who called whom) can be viewed as social networks, with phone numbers representing vertices and phone calls representing edges. Understanding a customer's social network can potentially provide a much better understanding of their behavior and preference. The technical challenge of this project is both statistical and computational. As the telecommunications industry serves a very large number of customers, their data sets are massive. In the single month, for example, a major telecommunications provider logged 12 billion phone calls made between 250 million phone numbers. The technical objectives are: 1) to further develop s nascent computational platform for extremely large-scale network analysis, and 2) to validate algorithms and procedures, which quantify the effectiveness of operator marketing campaigns. The goal is to create s software-and-services product offering designed to leverage telecom companies' own call logs to help them better value, serve and retain their customers. It is believed that the telecommunications industry has overlooked the richest data in their possession: the call logs themselves. A telecommunications operator has information not just on individuals, but on their calling behavior, their communities, and their communities' calling behavior. A single major operator typically serves over 15 million customers; given the sheer number of subscribers, operators must rely on statistical analysis to monitor customer satisfaction and to anticipate customer needs. Enhancing this knowledge will allow them to optimize their product marketing, to improve their customer care strategies, to more efficiently use their advertising budget, and to anticipate "churn," the cessation of service. The mobile phone market currently reaches over 4 billion subscribers globally. While the past decade has seen significant growth, most markets have reached saturation; mobile phone operators now are shifting their focus from growth to efficient customer retention strategies. This shift in strategy presents an opportunity to apply data mining techniques to call logs, a rich resource that to date has remained unused by the industry.

This project was described byAdmin Istrator (20. June 2011 - 11:35)
This project was last edited by Sanja Tumbas (6. July 2012 - 18:20)

Further information

This Project is related to the following Organization/s