ArticleFrontiers in psychology2022
The public information needs of COVID-19 vaccine: A study based on online Q&A communities and portals in China.
Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Article
- Article
- Attitudes of the public and medical professionals toward nurse prescribing: A text-mining study based on social medias.International journal of nursing sciences · 2024Article
- Public concerns and attitudes towards autism on Chinese social media based on K-means algorithm.Scientific reports · 2023Article
- The COVID-19 Infodemic on Twitter: A Space and Time Topic Analysis of the Brazilian Immunization Program and Public Trust.Tropical medicine and infectious disease · 2022Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: This study analyzes the topic and distribution features of public information needs for the COVID-19 vaccine from Chinese online Q&A communities and portals. It aims to identify the features and differences in public COVID-19 vaccine information needs at different periods. Design/Methodology: A total of 14,296 questions about the COVID-19 vaccine from four Chinese mainstream online communities and portals were studied following five procedures: data collection, data processing, K-means clustering, LDA topic model analysis, and needs identification. Findings: The study identified the topical features of public information needs for the COVID-19 vaccine during the first pandemic outbreak, pre-listing period, and post-listing period. It constructed a framework of public vaccine information needs. The information needs can be classified into 8 main categories and 16 subcategories. The eight main categories are vaccination (53.72%), evaluation and impact of other social events (17.90%), vaccine R&D and listing (9.49%), vaccine side effects and countermeasures (5.63%), vaccination necessity (4.98%), vaccine patent exemption (3.26%), vaccination effectiveness (2.94%), and essential knowledge of vaccine (2.08%), where percentage refers to the distribution of information needs data under various categories. Implications: Online communities and portals should provide dynamic and tailored information services according to changing public vaccine information needs. The public information needs regarding vaccination is prominent and should be addressed first. In the follow-up booster vaccination efforts, government health departments should prioritize susceptible groups, such as overseas students, airport workers, and healthcare workers. Originality/Value: We built a conceptual framework using data mining techniques and analyzed the COVID-19 vaccine information needs distribution at different time points and among different social groups, focusing on the theme of public information needs for the COVID-19 vaccine. It makes recommendations for government health departments and online platforms to improve the quality of COVID-19 vaccine information services for the public and provide a reference for the vaccination of COVID-19 booster shots.
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Registered trials
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