Analysis of Chinese Mainland Public Sentiment to the Novel Coronavirus Outbreak on Social Media
Jingxin Chen, Junfeng Xue, Bingke Zhu, Xinqi Hu, Ziqi Su, Xing Tao, Hongwei Lin · 2024
Social media platforms like Weibo have become crucial for disseminating information about the epidemic and assessing public sentiment. This study aims to comprehensively analyze Weibo posts related to novel coronavirus pneumonia to assist the government in guiding public sentiment and managing public opinion effectively. We collected over 1.1 million Weibo posts using web crawlers from December 27, 2019, to April 28, 2020. After preprocessing, we sorted keywords by TF-IDF and visualized them with word clouds. We identified public opinion hotspots and topics at each stage using LDA. Additionally, we conducted sentiment analysis across all stages and examined the characteristics of netizens’ sentiment trends and the evolution of public opinion. The results show that the novel coronavirus outbreak initially triggered strong negative emotions in the public, but effective governance measures helped mitigate these sentiments and positively influenced public emotions.