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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Acknowledgement
This study was supported by the State Key Laboratory of Media Convergence Production Technology and Systems, Beijing (Grand number SKLMCPTS2020003) and Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations.
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He, H. et al. (2022). Effects of Microblog Comments on Chinese User's Sentiment with COVID-19 Epidemic Topics. In: Rau, PL.P. (eds) Cross-Cultural Design. Applications in Business, Communication, Health, Well-being, and Inclusiveness. HCII 2022. Lecture Notes in Computer Science, vol 13313. Springer, Cham. https://doi.org/10.1007/978-3-031-06050-2_17
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