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Hot Topic Propagation Model and Opinion Leader Identifying Model in Microblog Network

Author

Listed:
  • Yan Lin
  • Huaxian Li
  • Xueqiao Liu
  • Suohai Fan

Abstract

As the network technique is fast developing, the microblog has been a significant carrier representing the social public opinions. Therefore, it is important to investigate the propagation characteristics of the topics and to unearth the opinion leaders in Micro‐blog network. The propagation status of the hot topics in the Micro‐blog is influenced by the authority of the participating individuals. We build a time‐varying model with the variational external field strength to simulate the topic propagation process. This model also fits for the multimodal events. The opinion leaders are important individuals who remarkably influence the topic discussions in its propagation process. They can help to guide the healthy development of public opinion. We build an AHP model based on the influence, the support, and the activity of a node, as well as a microblog‐rank algorithm based on the weighted undirected network, to unearth and analyze the opinion leaders’ characteristics. The experiments in the data, collected from the Sina Micro‐blog from October 2012 to November 2012 and from January 2013 to February 2013, show that our models predict the trend of hot topic efficiently and the opinion leaders we found are reasonable.

Suggested Citation

  • Yan Lin & Huaxian Li & Xueqiao Liu & Suohai Fan, 2013. "Hot Topic Propagation Model and Opinion Leader Identifying Model in Microblog Network," Abstract and Applied Analysis, John Wiley & Sons, vol. 2013(1).
    • Handle: RePEc:wly:jnlaaa:v:2013:y:2013:i:1:n:893961
    DOI: 10.1155/2013/893961
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    References listed on IDEAS

    as
    1. Qiang Yan & Lianren Wu & Chao Liu & Xiye Li, 2013. "Information Propagation in Online Social Network Based on Human Dynamics," Abstract and Applied Analysis, John Wiley & Sons, vol. 2013(1).
    2. Qiang Yan & Lianren Wu & Chao Liu & Xiye Li, 2013. "Information Propagation in Online Social Network Based on Human Dynamics," Abstract and Applied Analysis, Hindawi, vol. 2013, pages 1-6, May.
    3. Hema Yoganarasimhan, 2012. "Impact of social network structure on content propagation: A study using YouTube data," Quantitative Marketing and Economics (QME), Springer, vol. 10(1), pages 111-150, March.
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