Exploring the Expression Differences Between Professionals and Laypeople Toward the COVID-19 Vaccine: Text Mining...

Area of Science:

• Public Health
• Social Science
• Computational Linguistics

Background:

• COVID-19 vaccination is crucial for herd immunity, but public intention remains suboptimal.
• A notable divide exists between medical professionals' support and laypeople's suspicion towards COVID-19 vaccines.

Purpose of the Study:

• To analyze expression and thematic differences in COVID-19 vaccine discussions between professionals and laypeople using text mining.
• To understand public perception discrepancies regarding COVID-19 vaccines.

Main Methods:

• Collected 3196 answers from Zhihu forum discussions on COVID-19 vaccines.
• Categorized questions and respondents into professional and laypeople groups.
• Employed automated text analysis and Structural Topic Modeling (STM) to identify expression characteristics and thematic disparities.

Main Results:

• Laypeople dominated discussions; professionals provided longer answers and a conservative stance on vaccine effectiveness.
• Laypeople frequently mentioned countries and preferred topics on Chinese vaccine safety, while professionals focused on medical jargon and principles.
• No significant thematic differences were found regarding the social implications of vaccines.

Conclusions:

• Laypeople and professionals exhibit qualitatively different perspectives on COVID-19 vaccines, not quantitatively different knowledge.
• Understanding these cognitive differences is vital for public health practitioners to build consensus and promote vaccination.
• Web-based forums and STM are effective tools for analyzing public perception and group-specific topic preferences.