Research on Chinese Public Opinion on Releasing COVID-19 Prevention and Control Based on Improved LSTM

In December 2022, China gradually liberalized the control of COVID-19, which has caused a wide discussion in society. In this paper, Natural Language Processing (NLP) algorithm
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has been used to analyze online comment data on relevant topics on the SINA Weibo platform from November 2022 to March 2023. These data are related to the public's liberal views on COVID-19. This research is divided into three steps: (1) Use the Octopus Data Collector software to crawl the public opinion comment data in the SINA Weibo platform. Then, the crawled data has been cleaned, segmented, and manually annotated. At the same time, a marked data set has been obtained from the Paddle platform
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. (2) A total of 45,000 processed training data has been input into the Attention-Bi-LSTM model for training, and the optimal model has been selected based on the three evaluation indicators of Accuracy, F1-score, and Recall for subsequent sentimental prediction. (3) Finally, the model has been utilized to predict the remaining 24145 comment data. The analysis results showed that after the announcement of the release of COVID-19 Epidemic prevention and Control (COVID-19 EPC), the number of daily relevant comments on the SINA Weibo platform has declined, indicating that the life of the Chinese public has begun to shift toward a better situation. It is proven that it’s feasible to use an NLP algorithm to predict the sentiment of the online topic at a certain time, and it provides a potential method for the mining of the Chinese public's online public opinion.