Wang Lin, Xian Zuquan, Du Tianyu
Chinese Academy of Science and Education Evaluation, Hangzhou Dianzi University, Hangzhou, China.
School of Managment, Tianjin Normal University, Tianjin, China.
Front Psychol. 2022 Oct 10;13:961181. doi: 10.3389/fpsyg.2022.961181. eCollection 2022.
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.
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.
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.
本研究分析中国在线问答社区和门户网站中关于新冠疫苗公共信息需求的主题及分布特征。旨在识别不同时期公众对新冠疫苗信息需求的特点和差异。
设计/方法：按照数据收集、数据处理、K均值聚类、LDA主题模型分析和需求识别五个步骤，对来自中国四个主流在线社区和门户网站的14296个关于新冠疫苗的问题进行了研究。
该研究确定了新冠疫情首次爆发期间、上市前阶段和上市后阶段公众对新冠疫苗信息需求的主题特征。构建了公众疫苗信息需求框架。信息需求可分为8个主要类别和16个子类别。这八个主要类别分别是接种疫苗（53.72%）、其他社会事件的评估与影响（17.90%）、疫苗研发与上市（9.49%）、疫苗副作用及应对措施（5.63%）、接种疫苗的必要性（4.98%）、疫苗专利豁免（3.26%）、疫苗有效性（2.94%）以及疫苗基本知识（2.08%），其中百分比指各类别下信息需求数据的分布情况。
在线社区和门户网站应根据公众不断变化的疫苗信息需求，提供动态且量身定制的信息服务。公众对接种疫苗的信息需求较为突出，应优先予以满足。在后续的加强针接种工作中，政府卫生部门应将海外留学生、机场工作人员和医护人员等易感群体作为重点。
原创性/价值：我们运用数据挖掘技术构建了一个概念框架，分析了不同时间点以及不同社会群体对新冠疫苗信息需求的分布情况，重点关注公众对新冠疫苗信息需求的主题。为政府卫生部门和在线平台提高面向公众的新冠疫苗信息服务质量提供了建议，并为新冠疫苗加强针接种提供了参考。
