Analysis of Public Sentiment Evolution Mechanisms in Social Media Public Relations Crises

Authors

  • Yiyang Huang

DOI:

https://doi.org/10.61173/wbhkye30

Keywords:

Social media, public opinion crisis, public sentiment, sentiment evolution, public opinion governance

Abstract

With the increasingly widespread use of social media, public sentiment during crises in public opinion exhibits characteristics of rapid escalation, broad impact, and complex evolution, posing significant challenges to maintaining social stability and crisis management. This paper explores three dimensions: “theoretical foundations of emotional shifts,” “pathways and diffusion patterns of emotional transmission,” and “management intervention mechanisms for emotional dynamics.” Findings indicate that public sentiment eruptions stem from structural societal contradictions explained by the “social combustion theory.” Within crisis scenarios, individual cognitive evaluations and cognitive biases become catalysts for emotional escalation. The propagation of public sentiment on social media follows a phased, non-linear trajectory. Opinion leaders emotionally charged narratives, and platform-enabled amplification collectively constitute key channels for sentiment diffusion. Effective sentiment management interventions require coordinated efforts among multiple stakeholders—including governments, media, and the public—through systematic approaches such as disseminating authoritative information, promoting constructive journalism practices, and enhancing public media literacy. This study provides an integrated analytical framework for deepening understanding of the dynamic shifts in public sentiment in the digital age, while also offering theoretical reference points for related public opinion governance practices.

References

[1] Guo F. R. & Tong Y. Generation, characteristics, and mitigation strategies of collective emotions in online communities during emergencies. Journal of Shandong Technology and Business University, 2025, 39(02): 74-82.

[2] Ramos A. & Meeus L. Finding public outrage on social media during the Texas energy crisis. Energy Research & Social Science, 2024, 109: 103409.

[3] Zhu D. Q. & Wang G. H. Factors influencing the evolution of online social sentiment in hot public events: A case study of the “high-speed rail seat-hogging” incident. Journal of Information Science, 2020, 39(08): 94-100+116.

[4] Zhao Y. Z. & Xue T. Y. The transmission of panic sentiment and group cognition in crisis events. Contemporary Communication, 2021, 39(02): 31-35+40.

[5] Luo Baoyi, Zhang Bo. Integrated Mapping of Public Opinion Themes and Public Sentiment: Analysis of Public Sentiment in Sudden Public Crisis Events. News Knowledge, 2023, (09): 28- 39+94.

[6] Zhu Daiqiong, Wang Guohua. Influencing Factors and Mechanisms of Netizens’ Social Emotions During Emergencies: A Qualitative Comparative Analysis (QCA) Based on Triadic Interaction Determinism. Journal of Information Science, 2020, 39(03): 95-104.

[7] Yi Kui, Wang Yuqi, Xu Jun. Research on Empathy Transmission Mechanisms Among Internet “Circle” Users During Crisis Events: An Exploration Based on Dual Processes of Affective and Cognitive Empathy. Journal of Jiangxi Normal University (Philosophy and Social Sciences Edition), 2021, 54(03): 60-72.

[8] Shah A. M. & Schweiggart N. #BoycottMurree campaign on Twitter: Monitoring public response to negative destination events during a crisis. International Journal of Disaster Risk Reduction, 2023, 92: 103734.

[9] Theocharopoulos P. C., Tsoukala A., Georgakopoulos S. V., Tasoulis S. K., & Plagianakos V. P. Analysing sentiment change detection of Covid-19 tweets. Neural Computing and Applications, 2023, 35(29): 21433–21443.

[10] Chen X. Research on overseas online public opinion and sentiment analysis based on public safety event themes. Cyberspace Security, 2022, 13(04):78-85.

[11] Ammari T., Gutowska A., Ziff J., Randazzo C., & Subramonyam H. Retweets, Receipts, and Resistance: Discourse, Sentiment, and Credibility in Public Health Crisis Twitter (Version 1). arXiv, 2025.

[12] Wang H. Z., Qin Y. G., Shen M. Q., et al. Emotional Effects and Sentiment Guidance of Media Figurative Information Frames During Pandemics: An Emotion Content Analysis of Official Press Conferences in Beijing, Shanghai, and Guangzhou on Social Media Platforms. Nankai Management Review, 2023, 26(06): 224-236.

[13] Win Myint P. Y., Lo S. L., & Zhang Y. Unveiling the dynamics of crisis events: Sentiment and emotion analysis via multi-task learning with attention mechanism and subject-based intent prediction. Information Processing & Management, 2024, 61(4): 103695.

[14] Qing Wen, Wang Yibao, Jia Xiaojie, et al. Factors influencing public panic during crisis events and mitigation strategies: An empirical analysis based on early COVID-19 pandemic online survey data. Chinese Journal of Emergency Management Science, 2021, (11): 65-76.

[15] Wang Jiangpeng, Li Xiaoning. Public Emotion Governance in the Context of Constructive Journalism: An Examination Centered on Major Emergencies. Chinese Journal of Editing, 2021, (10): 16-19+24.

Downloads

Published

2025-12-19