Abstract: The research on the semantic expression of users’ vaccine sentiment and attitudes in Q&A platform can provide suggestions for relevant departments to make vaccine policy in China. This paper selects data from the vaccine community of “Zhihu”, a large online Q&A platform in China, and discusses the characteristics of the Q&A content from four aspects: vaccine sentiment, vaccine type, target population and information source through content analysis. It constructs the semantic networks from different vaccine sentiments, analyzes the network characteristics and core concepts, and discovers the theme differences between different networks. Studies have shown that social media is the main source of vaccine information, and there are lots of debates among young people and older about whether to inoculate vaccines that are not free. Compared with positive sentiment network and neutral sentiment network, the semantic network of negative sentiment is sparser and has fewer connections between concepts. Moreover, the concepts are often not concerned with the vaccination itself. The network contains many negative sentiment words and trust-related words such as vaccine scandal, government, institutions and so on. Adverse reactions and side effects after vaccination, distrust of vaccine pharmaceutical companies, dereliction of duty of government regulatory authorities, the impact of adverse vaccine events and the dishonesty of relevant media reports are the four main reasons for the public's negative sentiment, which affects their vaccine decisions and causes the vaccine hesitancy.

Key words: Online Q&A community, Semantic network analysis, Community detection, Vaccine sentiment, Vaccine hesitancy