Background: COVID-19 is still rampant all over the world. Until now, the COVID-19 vaccine is the most promising measure to subdue contagion and achieve herd immunity. However, public vaccination intention is suboptimal. A clear division lies between medical professionals and laypeople. While most professionals eagerly promote the vaccination campaign, some laypeople exude suspicion, hesitancy, and even opposition toward COVID-19 vaccines. Objective: This study aims to employ a text mining approach to examine expression differences and thematic disparities between the professionals and laypeople within the COVID-19 vaccine context. Methods: We collected 3196 answers under 65 filtered questions concerning the COVID-19 vaccine from the China-based question and answer forum Zhihu. The questions were classified into 5 categories depending on their contents and description: adverse reactions, vaccination, vaccine effectiveness, social implications of vaccine, and vaccine development. Respondents were also manually coded into two groups: professional and laypeople. Automated text analysis was performed to calculate fundamental expression characteristics of the 2 groups, including answer length, attitude distribution, and high-frequency words. Furthermore, structural topic modeling (STM), as a cutting-edge branch in the topic modeling family, was used to extract topics under each question category, and thematic disparities were evaluated between the 2 groups. Results: Laypeople are more prevailing in the COVID-19 vaccine–related discussion. Regarding differences in expression characteristics, the professionals posted longer answers and showed a conservative stance toward vaccine effectiveness than did laypeople. Laypeople mentioned countries more frequently, while professionals were inclined to raise medical jargon. STM discloses prominent topics under each question category. Statistical analysis revealed that laypeople preferred the “safety of Chinese-made vaccine” topic and other vaccine-related issues in other countries. However, the professionals paid more attention to medical principles and professional standards underlying the COVID-19 vaccine. With respect to topics associated with the social implications of vaccines, the 2 groups showed no significant difference. Conclusions: Our findings indicate that laypeople and professionals share some common grounds but also hold divergent focuses toward the COVID-19 vaccine issue. These incongruities can be summarized as “qualitatively different” in perspective rather than “quantitatively different” in scientific knowledge. Among those questions closely associated with medical expertise, the “qualitatively different” characteristic is quite conspicuous. This study boosts the current understanding of how the public perceives the COVID-19 vaccine, in a more nuanced way. Web-based question and answer forums are a bonanza for examining perception discrepancies among various identities. STM further exhibits unique strengths over the traditional topic modeling method in statistically testing the topic preference of diverse groups. Public health practitioners should be keenly aware of the cognitive differences between professionals and laypeople, and pay special attention to the topics with significant inconsistency across groups to build consensus and promote vaccination effectively.

Purpose: The mounting health misinformation on social media triggers heated discussions about how to address it. Anchored by the influence of presumed influence (IPI) model, this study investigates the underlying process of intentions to combat health misinformation. Specifically, we analyzed how presumed exposure of others and presumed influence on others affect intentions to practice pre-emptive and reactive misinformation countering strategies.Design/methodology/approach: Covariance-based structural equation modeling based on survey data from 690 Chinese participants was performed using the “lavaan” package in R to examine the proposed mechanism.Findings: Personal attention to health information on social media is positively associated with presumed others’ attention to the same information, which, in turn, is related to an increased perception of health misinformation’s influence on others. The presumed influence is further positively tied to two pre-emptive countermeasures (i.e. support for media literacy interventions and institutional verification intention) and one reactive countermeasure (i.e. misinformation correction intention). However, the relationship between presumed influence and support for governmental restrictions, as another reactive countering method, is not significant.Originality/value: This study supplements the misinformation countering literature by examining IPI’s tenability in explaining why individuals engage in combating misinformation. Both pre-emptive and reactive strategies were considered, enabling a panoramic view of the motivators of misinformation countering compared to previous studies. Our findings also inform the necessity of adopting a context-specific perspective and crafting other-oriented messages to motivate users’ initiative in implementing corrective actions.

More and more university students in China are opting to access, share, and comment on political issues via social media as a result of the rapid expansion of Internet technology. In the western part of China, you can find Western universities. University students there find it challenging to use the Internet and engage in online political activities due to the region’s level of economic development and social conventions. We are unsure whether their political involvement will have an effect on how society functions as a result. This study uses 530 students from Western colleges as a sample to investigate the effects of social media use on online political involvement and the adjustment effect of political efficacy. It combines a correlation analysis, multiple regression analysis, and regression multiples with a questionnaire survey. The results showed a strong positive link between Western Chinese university students’ online political participation and their use of social media. Students’ online political engagement in Western colleges greatly increased their political efficacy. Influence was governed by how effectively politics were perceived. This research can increase the political engagement of Western Chinese university students who utilize social media and offer some suggestions for how the government might carry out its daily operations to better control this activity.

Employing a sequential mixed-methods design combining survey (N = 607), interviews (N = 30), and digital ethnography, the study traces pathways from technology adoption to clinical interaction and introduces the concept of “algorithm-mediated negotiated authority.” Findings indicate that trust in generative AI arises from both perceived technical capability and socially conferred legitimacy, mediated by cognitive load. Health literacy and technology anxiety moderate this process, resulting in unequal empowerment. Authority is dynamically co-constructed as patients strategically introduce AI advice and physicians respond with explanatory, reassertive, or reserved strategies. Theoretically, the study bridges macro-level power critique with micro-behavioral analysis, advancing the “medical gaze” into a “negotiated gaze.” It extends technology acceptance models by emphasizing legitimacy construction and cognitive internalization, framing generative AI as a reconstructive force that reshapes clinical communication.

BACKGROUND COVID-19 is still rampant all over the world. Until now, the COVID-19 vaccine is the most promising measure to subdue contagion and achieve herd immunity. However, public vaccination intention is suboptimal. A clear division lies between medical professionals and laypeople. While most professionals eagerly promote the vaccination campaign, some laypeople exude suspicion, hesitancy, and even opposition toward COVID-19 vaccines. OBJECTIVE This study aims to employ a text mining approach to examine expression differences and thematic disparities between the professionals and laypeople within the COVID-19 vaccine context. METHODS We collected 3196 answers under 65 filtered questions concerning the COVID-19 vaccine from the China-based question and answer forum Zhihu. The questions were classified into 5 categories depending on their contents and description: adverse reactions, vaccination, vaccine effectiveness, social implications of vaccine, and vaccine development. Respondents were also manually coded into two groups: professional and laypeople. Automated text analysis was performed to calculate fundamental expression characteristics of the 2 groups, including answer length, attitude distribution, and high-frequency words. Furthermore, structural topic modeling (STM), as a cutting-edge branch in the topic modeling family, was used to extract topics under each question category, and thematic disparities were evaluated between the 2 groups. RESULTS Laypeople are more prevailing in the COVID-19 vaccine–related discussion. Regarding differences in expression characteristics, the professionals posted longer answers and showed a conservative stance toward vaccine effectiveness than did laypeople. Laypeople mentioned countries more frequently, while professionals were inclined to raise medical jargon. STM discloses prominent topics under each question category. Statistical analysis revealed that laypeople preferred the “safety of Chinese-made vaccine” topic and other vaccine-related issues in other countries. However, the professionals paid more attention to medical principles and professional standards underlying the COVID-19 vaccine. With respect to topics associated with the social implications of vaccines, the 2 groups showed no significant difference. CONCLUSIONS Our findings indicate that laypeople and professionals share some common grounds but also hold divergent focuses toward the COVID-19 vaccine issue. These incongruities can be summarized as “qualitatively different” in perspective rather than “quantitatively different” in scientific knowledge. Among those questions closely associated with medical expertise, the “qualitatively different” characteristic is quite conspicuous. This study boosts the current understanding of how the public perceives the COVID-19 vaccine, in a more nuanced way. Web-based question and answer forums are a bonanza for examining perception discrepancies among various identities. STM further exhibits unique strengths over the traditional topic modeling method in statistically testing the topic preference of diverse groups. Public health practitioners should be keenly aware of the cognitive differences between professionals and laypeople, and pay special attention to the topics with significant inconsistency across groups to build consensus and promote vaccination effectively.