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Product information diffusion in a social network

Author

Listed:
  • Ling Zhang

    (Wuhan University of Science and Technology)

  • Manman Luo

    (Wuhan University of Science and Technology)

  • Robert J. Boncella

    (Washburn University)

Abstract

There is a need to understand how to: spread product information to maximum range, identifying influential users, and analyze how they are intrinsically connected in a social network. In this paper, we collected tweets of Huawei Mate 9 to analyze users’ information behavior such as tweeting, forwarding, and commenting on tweets. We applied independent cascade model to this empirical Twitter diffusion network, and found it is proper to fit to the product information diffusion process. Using its network structure and PageRank measurement, we can identify influential nodes, and interpret the intrinsic connection between these influential nodes. Further, it is significant to consider the node’s background, such as interest, occupation, and country when identifying influential nodes. And it is discussed that the tweet content related to novel technology may attract more participation in ordinary users.

Suggested Citation

  • Ling Zhang & Manman Luo & Robert J. Boncella, 2020. "Product information diffusion in a social network," Electronic Commerce Research, Springer, vol. 20(1), pages 3-19, March.
    • Handle: RePEc:spr:elcore:v:20:y:2020:i:1:d:10.1007_s10660-018-9316-9
    DOI: 10.1007/s10660-018-9316-9
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    References listed on IDEAS

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    1. Daron Acemoglu & Asuman Ozdaglar, 2011. "Opinion Dynamics and Learning in Social Networks," Dynamic Games and Applications, Springer, vol. 1(1), pages 3-49, March.
    2. Hinz, Oliver & Skiera, Bernd & Barrot, Christian & Becker, Jan, 2011. "Seeding Strategies for Viral Marketing: An Empirical Comparison," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 56543, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. De Bruyn, Arnaud & Lilien, Gary L., 2008. "A multi-stage model of word-of-mouth influence through viral marketing," International Journal of Research in Marketing, Elsevier, vol. 25(3), pages 151-163.
    4. Réka Albert & Hawoong Jeong & Albert-László Barabási, 1999. "Diameter of the World-Wide Web," Nature, Nature, vol. 401(6749), pages 130-131, September.
    5. Duncan J. Watts & Peter Sheridan Dodds, 2007. "Influentials, Networks, and Public Opinion Formation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(4), pages 441-458, May.
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    Cited by:

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    2. Rybaczewska Maria & Chesire Betty Jebet & Sparks Leigh, 2020. "YouTube Vloggers as Brand Influencers on Consumer Purchase Behaviour," Journal of Intercultural Management, Sciendo, vol. 12(3), pages 117-140, September.
    3. Satish Kumar & Weng Marc Lim & Nitesh Pandey & J. Christopher Westland, 2021. "20 years of Electronic Commerce Research," Electronic Commerce Research, Springer, vol. 21(1), pages 1-40, March.

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