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Trend Prediction of Event Popularity from Microblogs

Author

Listed:
  • Xujian Zhao

    (School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang 621010, China)

  • Wei Li

    (School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang 621010, China)

Abstract

Owing to rapid development of the Internet and the rise of the big data era, microblog has become the main means for people to spread and obtain information. If people can accurately predict the development trend of a microblog event, it will be of great significance for the government to carry out public relations activities on network event supervision and guide the development of microblog event reasonably for network crisis. This paper presents effective solutions to deal with trend prediction of microblog events’ popularity. Firstly, by selecting the influence factors and quantifying the weight of each factor with an information entropy algorithm, the microblog event popularity is modeled. Secondly, the singular spectrum analysis is carried out to decompose and reconstruct the time series of the popularity of microblog event. Then, the box chart method is used to divide the popularity of microblog event into various trend spaces. In addition, this paper exploits the Bi-LSTM model to deal with trend prediction with a sequence to label model. Finally, the comparative experimental analysis is carried out on two real data sets crawled from Sina Weibo platform. Compared to three comparative methods, the experimental results show that our proposal improves F1-score by up to 39%.

Suggested Citation

  • Xujian Zhao & Wei Li, 2021. "Trend Prediction of Event Popularity from Microblogs," Future Internet, MDPI, vol. 13(9), pages 1-13, August.
    • Handle: RePEc:gam:jftint:v:13:y:2021:i:9:p:220-:d:621078
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    References listed on IDEAS

    as
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