Investigating the Public Sentiment in Major Public Emergencies Through the Complex Networks Method: A Case Study of COVID-19 Epidemic - Yang, Guang; Wang, Zhidan; Chen, Lin (Frontiers in Public Health, 2022)
The main purpose of this study is to investigate what topic indicators correlate with public sentiment during the “COVID-19 epidemic” and which indicators control the complex networks of the topic indicators. We obtained 68,098 Weibo, categorized them into 11 topic indicators, and grouped these indicators into three dimensions. Then we constructed the complex networks model of the Weibo’s topics and examined the key indicators affecting the public’s sentiment during the major public emergency. The results showed that “positive emotion” is positively correlated with “recordings of epidemic” and “foreign comparisons”, while “negative emotion” is negatively correlated with “government image”, “recordings of epidemic” and “asking for help online”. In addition, the two vertexes of “recordings of epidemic” and “foreign comparisons” are the most important “bridges” which connect the government and the public. The “recordings of epidemic” is the main connection “hub” between the government and the media. In other words, the “recordings of epidemic” is the central topic indicator that controls the entire topic networks. In conclusion, the government should publish the advance of the events through official media in a timely manner and transparent way and create a platform where everyone can speak directly to government for advice and assistance during the major public emergency in the future.