Since the COVID-19 pandemic started, scholars have been researching and publishing their studies in various fields. In social sciences, some researchers used DiVoMiner® to understand how the public coped with stress during the pandemic with content analysis approach; some researchers collected online posts and evaluated the public opinion on the pandemic in Taiwan with the aid of DiVoMiner®; and another research tapped into the vaccine effectiveness discussion on social networks during the outbreak…Here is a list of articles that used DiVoMiner® to facilitate their Coronavirus (COVID-19) research. Check it out!
- Chang, A., Ho, M. (2022 March 12). Heightening fake information and misinformation around COVID-19 vaccine controversy by examining super-spreaders’ lies. Fake Information and Global Communication. Shanghai International Studies University, Shanghai, China & Online meeting. https://repository.um.edu.mo/handle/10692/111329
- Gao, H., Zhao, Q., Ning, C., Guo, D., Wu, J., Li, L. (2022). Does the COVID-19 Vaccine Still Work That “Most of the Conﬁrmed Cases Had Been Vaccinated”? A Content Analysis of Vaccine Effectiveness Discussion on Sina Weibo during the Outbreak of COVID-19 in Nanjing. J. Environ. Res. Public Health 9/241. https://doi.org/10.3390/ijerph19010241
- Chang, A., Xian, X., Liu, M. T., & Zhao, X. (2022). Health communication through positive and solidarity messages amid the COVID-19 pandemic: Automated content analysis of facebook uses. International Journal of Environmental Research and Public Health, 19(10), 6159. doi: https://doi.org/10.3390/ijerph19106159
- Tu, S., Lu, L. Y., Hsieh, C., & Wu, C. (2021). A New Internet Public Opinion Evaluation Model: A Case Study of Public Opinions on COVID-19 in Taiwan. International Journal of Big Data and Analytics in Healthcare (IJBDAH), 6(2), 1-17. http://doi.org/10.4018/IJBDAH.287603
- Chang, A., Schulz, P. J., Tu, S., & Liu, M. T. (2020). Communicative Blame in Online Communication of the COVID-19 Pandemic: Computational Approach of Stigmatizing Cues and Negative Sentiment Gauged With Automated Analytic Techniques. Journal of Medical Internet Research, 22(11), e21504. URL: https://www.jmir.org/2020/11/e21504. DOI: 10.2196/21504