Background: China is at the forefront of global efforts to develop COVID-19 vaccines and has five fast-tracked candidates at the final-stage, large-scale human clinical trials testing phase. Vaccine-promoting policymaking for public engagement is a prerequisite for social mobilization. However, making an informed and judicious choice is a dilemma for the Chinese government in the vaccine promotion context. Objective: In this study, public opinions in China were analyzed via dialogues on Chinese social media, based on which Chinese netizens’ views on COVID-19 vaccines and vaccination were investigated. We also aimed to develop strategies for promoting vaccination programs in China based on an in-depth understanding of the challenges in risk communication and social mobilization. Methods: We proposed a novel behavioral dynamics model, SRS/I (susceptible-reading-susceptible/immune), to analyze opinion transmission paradigms on Chinese social media. Coupled with a meta-analysis and natural language processing techniques, the emotion polarity of individual opinions was examined in their given context. Results: We collected more than 1.75 million Weibo messages about COVID-19 vaccines from January to October 2020. According to the public opinion reproduction ratio (R0), the dynamic propagation of those messages can be classified into three periods: the ferment period (R01=1.1360), the revolution period (R02=2.8278), and the transmission period (R03=3.0729). Topics on COVID-19 vaccine acceptance in China include price and side effects. From September to October, Weibo users claimed that the vaccine was overpriced, making up 18.3% (n=899) of messages; 38.1% (n=81,909) of relevant topics on Weibo received likes. On the contrary, the number of messages that considered the vaccine to be reasonably priced was twice as high but received fewer likes, accounting for 25.0% (n=53,693). In addition, we obtained 441 (47.7%) positive and 295 (31.9%) negative Weibo messages about side effects. Interestingly, inactivated vaccines instigated more heated discussions than any other vaccine type. The discussions, forwards, comments, and likes associated with topics related to inactivated vaccines accounted for 53% (n=588), 42% (n=3072), 56% (n=3671), and 49% (n=17,940), respectively, of the total activity associated with the five types of vaccines in China. Conclusions: Most Chinese netizens believe that the vaccine is less expensive than previously thought, while some claim they cannot afford it for their entire family. The findings demonstrate that Chinese individuals are inclined to be positive about side effects over time and are proud of China’s involvement with vaccine development. Nevertheless, they have a collective misunderstanding about inactivated vaccines, insisting that inactivated vaccines are safer than other vaccines. Reflecting on netizens’ collective responses, the unfolding determinants of COVID-19 vaccine acceptance provide illuminating benchmarks for vaccine-promoting policies.

Sentiment lexicon, which provides sentiment information for words, plays an important role in sentiment analysis task. Currently, most of sentiment lexicons have only one sentiment polarity for each word and ignore sentimental ambiguity. In this paper, we propose to construct the sentiment lexicon based on context-dependent part-of-speech (POS) chunks, namely CP-chunks, which aims at solving the ambiguity of lexical sentiments. Given that the POS of context has impact on the word polarity and intensity, we take CP-chunks as an unit to do sentiment calculation. Our method is evaluated through the classification task of text sentiment. The experiment results indicate that, in comparison with the existing methods, the applicability of our method is more stable and balanced for both the positive and negative polarities corpora, and the accuracy of our method reaches 82% for the sentiment classification of a domain-specific corpus.

In the context of the COVID-19 pandemic, global vaccine campaigns are a mass vaccination intervention conducted through routine service provision for individuals who have reached a specified age. However, obtaining a high uptake rate to reach herd immunity may be undermined by various social motivations. To scrutinize the practical and dynamic strategies for a successful vaccination campaign, we map out the determinants that exacerbate vaccine hesitancy by leveraging the capacity of rich metadata from Twitter. Here, we uncover the collective propensities underlying dynamic social motivations and the uneven distribution of vaccines across the globe. Our findings suggest that profiling the status quo of public perceptions and engaging in introspection about vaccine-promoting policies in due course are integral components of preparedness against the ongoing pandemic. Simultaneously, we propose several recommendations to remind governments of the importance of building confidence in vaccination in a targeted way, and we assert that national barriers should be abandoned and that international responsibility should be assumed.