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Factors dominating individual information disseminating behavior on social networking sites

Author

Listed:
  • Juan Shi

    (Xi’an Jiaotong University
    City University of Hong Kong)

  • Kin Keung Lai

    (City University of Hong Kong
    Shaanxi Normal University)

  • Ping Hu

    (Xi’an Jiaotong University)

  • Gang Chen

    (China Shipbuilding Industry Corporation)

Abstract

Identifying dominating features that affect individual information retweeting behavior on social networking sites (SNSs) is crucial to understanding individual retweeting behaivor and developing effective marketing strategies on SNS. However, there is little agreement on what factors are dominating individual information disseminating behavior on SNS, and what’s worse, more and more factors are added into the prediction model, without examining the relevance of them and even why these factors are added is rarely discussed. This leads to undesirable outcomes such as increasing the cost of measuring and computing irrelevant/redundant features. Most importantly, it hinders us from understanding what discriminative features are affecting individual information disseminating behavior. Using a unique real-life Twitter data set consisting of 55,575 twitterers and 9,440,321 tweets, the authors examine what discriminative features are dominating individual information disseminating behavior. The results indicate that topic distance is the most discriminative factor, highlighting that self-presentation motives play an important role in information disseminating decisions. Besides, the amount of information, social relationship and the popularity of the tweet also contribute to individual information disseminating decisions. Experiments demonstrate that adopting only dominating factors can improve prediction performance in terms of various indicators, compared with adopting the full features set. Finally, we conclude the paper by discussing theoretical and practical implications of our findings.

Suggested Citation

  • Juan Shi & Kin Keung Lai & Ping Hu & Gang Chen, 2018. "Factors dominating individual information disseminating behavior on social networking sites," Information Technology and Management, Springer, vol. 19(2), pages 121-139, June.
    • Handle: RePEc:spr:infotm:v:19:y:2018:i:2:d:10.1007_s10799-017-0278-8
    DOI: 10.1007/s10799-017-0278-8
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    References listed on IDEAS

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    1. Gupta, Pranjal & Harris, Judy, 2010. "How e-WOM recommendations influence product consideration and quality of choice: A motivation to process information perspective," Journal of Business Research, Elsevier, vol. 63(9-10), pages 1041-1049, September.
    2. 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.
    3. Scott Deerwester & Susan T. Dumais & George W. Furnas & Thomas K. Landauer & Richard Harshman, 1990. "Indexing by latent semantic analysis," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(6), pages 391-407, September.
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    Cited by:

    1. Mehdi Darban & Minsun Kim & Ahmet Koksal, 2021. "When the technology abandonment intentions remitted: the case of herd behavior," Information Technology and Management, Springer, vol. 22(3), pages 163-178, September.

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