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Information propagation in online social networks: a tie-strength perspective

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Abstract

In this paper, we investigate the relationship between the tie strength and information propagation in online social networks (OSNs). Specifically, we propose a novel information diffusion model to simulate the information propagation in OSNs. Empirical studies through this model on various real-world online social network data sets reveal three interesting findings. First, it is the adoption of the information pushing mechanism that greatly facilitates the information propagation in OSNs. Second, some global but cost-intensive strategies, such as selecting the ties of higher betweenness centralities for information propagation, no longer have significant advantages. Third, the random selection strategy is more efficient than selecting the strong ties for information propagation in OSNs. Along this line, we provide further explanations by categorizing weak ties into positive and negative ones and reveal the special bridge effect of positive weak ties. The inverse quantitative relationship between weak ties and network clustering coefficients is also carefully studied, which finally gives reasonable explanations to the above findings. Finally, we give some business suggestions for the cost-efficient and secured information propagation in online social networks.

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Authors and Affiliations

  1. State Key Laboratory of Software Development Environment, Beihang University, Beijing, China

    Jichang Zhao, Xu Feng & Ke Xu

  2. School of Economics and Management, Beihang University, Beijing, China

    Junjie Wu

  3. Rutgers Business School, Rutgers University, New Brunswick, NJ, USA

    Hui Xiong

Authors
  1. Jichang Zhao
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  2. Junjie Wu
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  3. Xu Feng
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  4. Hui Xiong
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  5. Ke Xu
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Corresponding author

Correspondence to Ke Xu.

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Zhao, J., Wu, J., Feng, X. et al. Information propagation in online social networks: a tie-strength perspective. Knowl Inf Syst 32, 589–608 (2012). https://doi.org/10.1007/s10115-011-0445-x

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