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A Topological Approach for Detecting Twitter Communities with Common Interests

  • Conference paper
Ubiquitous Social Media Analysis (MUSE 2012, MSM 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8329))

Abstract

The efficient identification of communities with common interests is a key consideration in applying targeted advertising and viral marketing to online social networking sites. Existing methods involve large scale community detection on the entire social network before determining the interests of individuals within these communities. This approach is both computationally intensive and may result in communities without a common interest. We propose an efficient topological-based approach for detecting communities that share common interests on Twitter. Our approach involves first identifying celebrities that are representative of an interest category before detecting communities based on linkages among followers of these celebrities. We also study the network characteristics and tweeting behaviour of these communities, and the effects of deepening or specialization of interest on their community structures. In particular, our evaluation on Twitter shows that these detected communities comprise members who are well-connected, cohesive and tweet about their common interest.

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Author information

Authors and Affiliations

  1. School of Computer Science and Software Engineering, The University of Western Australia, Crawley, WA, 6009, Australia

    Kwan Hui Lim & Amitava Datta

Authors
  1. Kwan Hui Lim
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  2. Amitava Datta
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Editor information

Editors and Affiliations

  1. Knowledge and Data Engineering Group, University of Kassel, Wilhelmshöher Allee 73, 34121, Kassel, Germany

    Martin Atzmueller

  2. Economic and Technological Development Area, Nokia, Building 2, N. 5 Donghuan Zhonglu, Economic and Technological Development Area, 100176,, Beijing, China

    Alvin Chin

  3. Institute for Knowledge Management, Graz University of Technology, Inffeldgasse 21a, 8010, Graz, Austria

    Denis Helic

  4. Data Mining and Information Retrieval Group, University of Würzburg, Am Hubland, 97074, Würzburg, Germany

    Andreas Hotho

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Lim, K.H., Datta, A. (2013). A Topological Approach for Detecting Twitter Communities with Common Interests. In: Atzmueller, M., Chin, A., Helic, D., Hotho, A. (eds) Ubiquitous Social Media Analysis. MUSE MSM 2012 2012. Lecture Notes in Computer Science(), vol 8329. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45392-2_2

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  • DOI: https://doi.org/10.1007/978-3-642-45392-2_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-45391-5

  • Online ISBN: 978-3-642-45392-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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