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Social Network Analysis in Streaming Call Graphs

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Big Data Analysis: New Algorithms for a New Society

Part of the book series: Studies in Big Data ((SBD,volume 16))

Abstract

Mobile phones are powerful tools to connect people. The streams of Call Detail Records (CDR’s) generating from these devices provide a powerful abstraction of social interactions between individuals, representing social structures. Call graphs can be deduced from these CDRs, where nodes represent subscribers and edges represent the phone calls made. These graphs may easily reach millions of nodes and billions of edges. Besides being large-scale and generated in real-time, the underlying social networks are inherently complex and, thus, difficult to analyze. Conventional data analysis performed by telecom operators is slow, done by request and implies heavy costs in data warehouses. In face of these challenges, real-time streaming analysis becomes an ever increasing need to mobile operators, since it enables them to quickly detect important network events and optimize business operations. Sampling, together with visualization techniques, are required for online exploratory data analysis and event detection in such networks. In this chapter, we report the burgeoning body of research in network sampling, visualization of streaming social networks, stream analysis and the solutions proposed so far.

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Acknowledgments

This work was supported by Sibila and Smartgrids research projects (NORTE-07-0124-FEDER-000056/59), financed by North Portugal Regional Operational Programme (ON.2 O Novo Norte), under the National Strategic Reference Framework (NSRF), through the Development Fund (ERDF), and by national funds, through the Portuguese funding agency, Fundação para a Ciência e a Tecnologia (FCT), and by European Commission through the project MAESTRA (Grant number ICT-2013-612944). The authors also acknowledge the financial support given by the project number 18450 through the “SI I&DT Individual” program by QREN and delivered to WeDo Business Assurance. Márcia Oliveira gratefully acknowledges funding from FCT, through Ph.D. grant SFRH/BD/81339/2011.

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Authors and Affiliations

  1. LIAAD/INESC TEC, University of Porto, Porto, Portugal

    Rui Sarmento, Márcia Oliveira, Mário Cordeiro, Shazia Tabassum & João Gama

  2. FEP, School of Economics and Management, University of Porto, Porto, Portugal

    Rui Sarmento, Márcia Oliveira & João Gama

Authors
  1. Rui Sarmento
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  2. Márcia Oliveira
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  3. Mário Cordeiro
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  4. Shazia Tabassum
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  5. João Gama
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Correspondence to João Gama .

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Editors and Affiliations

  1. University of Ottawa, Ottawa, Ontario, Canada

    Nathalie Japkowicz

  2. Institute of Computing Sciences, Poznań University of Technology, Poznań, Poland

    Jerzy Stefanowski

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Sarmento, R., Oliveira, M., Cordeiro, M., Tabassum, S., Gama, J. (2016). Social Network Analysis in Streaming Call Graphs. In: Japkowicz, N., Stefanowski, J. (eds) Big Data Analysis: New Algorithms for a New Society. Studies in Big Data, vol 16. Springer, Cham. https://doi.org/10.1007/978-3-319-26989-4_10

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  • DOI: https://doi.org/10.1007/978-3-319-26989-4_10

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