Abstract
Social media is one of the most significant sources of information in modern people’s life. Due to the large quantity of user base and public opinions, when people read a blog post, the different tendencies of comments may affect their views on the event to a certain extent. This paper, taking the COVID-19 epidemic as an example, investigated the impact of Weibo (a popular social software in China) comments on readers’ sentiments. In this paper, text mining technology was adopted to collect data including the blogs and the comments under each blog, and the NLPIR-Parser platform was used to analyze the sentiment of the comments. Finally, the conclusion that the sentiments of other comments tend to follow the sentiments of the first comments was drawn. Based on the research results, this paper also gave some enlightenment on social media management and suggestions of public opinions oversight.
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CITATION STYLE
He, H., Guo, Z., Zhan, J., Fan, P., Xia, Y., Wang, M., … Chen, Z. (2022). Effects of Microblog Comments on Chinese User’s Sentiment with COVID-19 Epidemic Topics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13313 LNCS, pp. 230–240). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-06050-2_17
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