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VLDB Workshop on Big Graphs Online Querying

VLDB Workshop on Data Management and Analytics for Medicine and Healthcare

Big-O(Q) 2015, DMAH 2015: Biomedical Data Management and Graph Online Querying pp 149–154Cite as

Social Network Analytics: Beyond the Obvious

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9579))

Abstract

Over the last decade and a half, there has been an explosion of interest in the analysis and mining of very large networks, including those arising in social and information networks, biological networks such as protein-protein interaction networks, web graph, collaboration networks, customer-product interaction networks, and road networks, to name a few. The interest has been fueled by driving applications as well as by the unprecedented availability of real network data. Of particular note among the driving applications are the study of spread of infections and innovations, word-of-mouth marketing or the so-called viral marketing, and tracking of events and stories in social media. In this talk, I will use viral marketing and event and story evolution tracking as concrete settings with which to describe some exciting research that has been done over the past several years. In the process, I will briefly discuss some less obvious applications of mining large graphs.

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Author information

Authors and Affiliations

  1. University of British Columbia, Vancouver, BC, Canada

    Laks V. S. Lakshmanan

Authors
  1. Laks V. S. Lakshmanan
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Corresponding author

Correspondence to Laks V. S. Lakshmanan .

Editor information

Editors and Affiliations

  1. Stony Brook University, Stony Brook, New York, USA

    Fusheng Wang

  2. University of Utah, Salt Lake City, Utah, USA

    Gang Luo

  3. Columbia University, New York, New York, USA

    Chunhua Weng

  4. Nanyang Technological University, Singapore, Singapore

    Arijit Khan

  5. Qatar Computing Research Institute, Doha, Qatar

    Prasenjit Mitra

  6. Google Research, New York, New York, USA

    Cong Yu

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© 2016 Springer International Publishing Switzerland

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Lakshmanan, L.V.S. (2016). Social Network Analytics: Beyond the Obvious. In: Wang, F., Luo, G., Weng, C., Khan, A., Mitra, P., Yu, C. (eds) Biomedical Data Management and Graph Online Querying. Big-O(Q) DMAH 2015 2015. Lecture Notes in Computer Science(), vol 9579. Springer, Cham. https://doi.org/10.1007/978-3-319-41576-5_11

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  • DOI: https://doi.org/10.1007/978-3-319-41576-5_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41575-8

  • Online ISBN: 978-3-319-41576-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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