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Identifying the main paths of information diffusion in online social networks

Author

Listed:
  • Zhu, Hengmin
  • Yin, Xicheng
  • Ma, Jing
  • Hu, Wei

Abstract

Recently, an increasing number of researches on relationship strength show that there are some socially active links in online social networks. Furthermore, it is likely that there exist main paths which play the most significant role in the process of information diffusion. Although much of previous work has focused on the pathway of a specific event, there are hardly any scholars that have extracted the main paths. To identify the main paths of online social networks, we proposed a method which measures the weights of links based on historical interaction records. The influence of node based on forwarding amount is quantified and top-ranked nodes are selected as the influential users. The path importance is evaluated by calculating the probability that a message would spread via this path. We applied our method to a real-world network and found interesting insights. Each influential user can access another one via a short main path and the distribution of main paths shows significant community effect.

Suggested Citation

  • Zhu, Hengmin & Yin, Xicheng & Ma, Jing & Hu, Wei, 2016. "Identifying the main paths of information diffusion in online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 320-328.
    • Handle: RePEc:eee:phsmap:v:452:y:2016:i:c:p:320-328
    DOI: 10.1016/j.physa.2016.01.048
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    References listed on IDEAS

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    Cited by:

    1. Liu, Xiaoyang & He, Daobing & Liu, Chao, 2018. "Modeling information dissemination and evolution in time-varying online social network based on thermal diffusion motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 456-476.
    2. Li, Kai & Zhu, Hengmin & Zhang, Yihan & Wei, Jing, 2022. "Dynamic evaluation method on dissemination capability of microblog users based on topic segmentation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    3. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.

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