Abstract
The Coronavirus Disease 2019 has a huge impact on countries all over the world. The analysis of public opinions during this period is conducive to the government timely understanding and solving the difficulties faced by the people. In this paper, we crawled text data from different periods of “Wuhan lockdown” and “Wuhan lift lockdown” from Sina Weibo for analysis. Then we use LDA topic modeling and LDAvis visualization methods to compare the topics that people pay attention to in different periods. We find that people’s concerns are indeed different in different periods. Therefore, public opinion analysis can enable decision-makers to understand a large amount of information in a short time, and the government can establish a good relationship with the public by solving hot and difficult issues of public concern. By analyzing the public opinions during the epidemic in China, we can also know the corresponding measures taken by the Chinese government. At present, many countries in the world are deeply affected by the epidemic, and this paper also provides reference for the reconstruction of these countries.
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Acknowledgements
This study is supported by Guangdong Province Soft Science Project (2019A101002075), Guangdong Province Educational Science Plan 2019 (2019JKCY010), Guangdong Province Bachelor and Postgraduate Education Innovation Research Project (2019SFKC46).
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Chen, L., Huang, X., Zhang, H., Niu, B. (2020). Covid-19 Public Opinion Analysis Based on LDA Topic Modeling and Data Visualization. In: Chen, X., Yan, H., Yan, Q., Zhang, X. (eds) Machine Learning for Cyber Security. ML4CS 2020. Lecture Notes in Computer Science(), vol 12487. Springer, Cham. https://doi.org/10.1007/978-3-030-62460-6_20
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DOI: https://doi.org/10.1007/978-3-030-62460-6_20
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