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Research Progress and Hotspots in Epidemics and Public Opinion: Visual Review Based on CiteSpace

DOI: 10.4236/ajc.2023.112008, PP. 106-115

Keywords: Epidemics, Public Opinion, Visual Review

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Abstract:

The paper aims to present a comprehensive analysis of the progress, hotspots, and trends of research in the study of epidemics and public opinion. Using CiteSpace as a research tool, this study focuses on 102 relevant literature on epidemics and public opinion published between 2013 and 2023 in the core database of Web of Science. Drawing on various data such as the annual number of publications, journal sources, authors, research institutions, and keywords, this paper constructs knowledge maps to provide an in-depth analysis of the research trends and developmental directions in the field of study over the past decade. The research findings indicate that the field of study has undergone three phases, namely exploration, outbreak, and retracement. The research hotspots in this field of study mainly focus on social media, epidemics model, media, public health, sentiment analysis, Twitter, behavior, and communication. Additionally, the research highlights that online public opinion is an essential trend for future exploration and study in this field.

References

[1]  Han, X., Wang, J., Zhang, M., & Wang, X. (2020). Using Social Media to Mine and Analyze Public Opinion Related to COVID-19 in China. International Journal of Environmental Research and Public Health, 17, 2788.
https://doi.org/10.3390/ijerph17082788
[2]  Li, J., Ma, Y., Xu, X., Pei, J., & He, Y. (2022). A Study on Epidemic Information Screening, Prevention and Control of Public Opinion Based on Health and Medical Big Data: A Case Study of COVID-19. International Journal of Environmental Research and Public Health, 19, 9819.
https://doi.org/10.3390/ijerph19169819
[3]  Moussaïd, M., Kämmer, J. E., Analytis, P. P., & Neth, H. (2013). Social Influence and the Collective Dynamics of Opinion Formation. PLOS ONE, 8, e78433.
https://doi.org/10.1371/journal.pone.0078433
[4]  Naseem, U., Razzak, M. I., Khushi, M., Eklund, P. W., & Kim, J. (2021). COVIDSenti: A Large-Scale Benchmark Twitter Data Set for COVID-19 Sentiment Analysis. IEEE Transactions on Computational Social Systems, 8, 1003–1015.
https://doi.org/10.1109/TCSS.2021.3051189
[5]  Nian, F., Guo, X., & Li, J. (2021). A New Spreading Model in the Environment of Epidemic-Related Online Rumors. Modern Physics Letters B, 36, Article ID: 2150569.
https://doi.org/10.1142/S0217984921505692
[6]  Sabat, I., Neumann-Böhme, S., Varghese, N. E., Barros, P. P., Brouwer, W. B. F., Van Exel, J., Schreyögg, J., & Stargardt, T. (2020). United but Divided: Policy Responses and People’s Perceptions in the EU during the COVID-19 Outbreak. Health Policy, 124, 909-918.
https://doi.org/10.1016/j.healthpol.2020.06.009
[7]  Wu, J., Ni, S., & Shen, S. (2016). Dynamics of Public Opinion under the Influence of Epidemic Spreading. International Journal of Modern Physics C, 27, Article ID: 1650079.
https://doi.org/10.1142/S0129183116500790
[8]  Yang, K., Zhu, J., Yang, L., Lin, Y., Huang, X., & Li, Y. (2023). Analysis of Network Public Opinion on COVID-19 Epidemic Based on the WSR Theory. Frontiers in Public Health, 10, Article ID: 1104031.
https://doi.org/10.3389/fpubh.2022.1104031
[9]  Zhang, C., Ma, N., & Sun, G. (2022). Using Grounded Theory to Identify Online Public Opinion in China to Improve Risk Management—The Case of COVID-19. International Journal of Environmental Research and Public Health, 19, 14754.
https://doi.org/10.3390/ijerph192214754
[10]  Zhang, X., Zhou, Y., Zhou, F., & Pratap, S. (2021). Internet Public Opinion Dissemination Mechanism of COVID-19: Evidence from the Shuanghuanglian Event. Data Technologies and Applications, 56, 283-302.
https://doi.org/10.1108/DTA-11-2020-0275
[11]  Zhao, Y., Cheng, S., Yu, X., & Xu, H. (2020). Chinese Public’s Attention to the COVID-19 Epidemic on Social Media: Observational Descriptive Study. Journal of Medical Internet Research, 22, e18825.
https://doi.org/10.2196/18825

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