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Measuring and profiling the topical influence and sentiment contagion of public event stakeholders

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  • An, Lu
  • Zhou, Wenjing
  • Ou, Menghua
  • Li, Gang
  • Yu, Chuanming
  • Wang, Xiaofen

Abstract

When public events occur, users often generate a huge number of microblog entries and their online interactions with one another. Forwarding and commenting on posts contribute to the huge networks of topic and sentiment communication. This study constructs the topic and sentiment propagation maps of microblogging in the context of public events to visually explore the patterns of topic and sentiment propagation among stakeholders across different phases. To quantify the influence of topic and sentiment propagation, four indicators of “topic out-degree,” “topic variation degree,” “sentiment out-degree,” and “sentiment deviation degree” are proposed. We chose the child abuse case in the Beijing Red-Yellow-Blue (RYB) Kindergarten for our study. The positions of various stakeholders in the propagation paths and the relationship among stakeholders were revealed. Results indicate that the government and mainstream media have the greatest influence in terms of topic and sentiment propagation. Moreover, topic propagation was the most influential in the recession phase and the same can be said with sentiment propagation in the spreading phase. The findings can help the emergency management departments gain a better understanding of the propagation patterns of topics and emotions and the role of stakeholders in such phenomena to improve their emergency response ability.

Suggested Citation

  • An, Lu & Zhou, Wenjing & Ou, Menghua & Li, Gang & Yu, Chuanming & Wang, Xiaofen, 2021. "Measuring and profiling the topical influence and sentiment contagion of public event stakeholders," International Journal of Information Management, Elsevier, vol. 58(C).
  • Handle: RePEc:eee:ininma:v:58:y:2021:i:c:s0268401221000207
    DOI: 10.1016/j.ijinfomgt.2021.102327
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    Citations

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    Cited by:

    1. Guanghui Wang & Yushan Wang & Kaidi Liu & Shu Sun, 2024. "A classification and recognition algorithm of key figures in public opinion integrating multidimensional similarity and K-shell based on supernetwork," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-19, December.
    2. Meijie Chu & Wentao Song & Zeyu Zhao & Tianmu Chen & Yi-chen Chiang, 2024. "Emotional contagion on social media and the simulation of intervention strategies after a disaster event: a modeling study," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    3. Meng Cai & Han Luo & Xiao Meng & Ying Cui & Wei Wang, 2022. "Influence of information attributes on information dissemination in public health emergencies," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-22, December.
    4. Zhihang Liu & Jinlin Wu & Connor Y. H. Wu & Xinming Xia, 2024. "Shifting sentiments: analyzing public reaction to COVID-19 containment policies in Wuhan and Shanghai through Weibo data," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.

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