Park Sunyoung
Department of Psychiatry, National Health Insurance Service Ilsan Hospital, Goyang-si, Gyeonggi-do, 10444, South Korea.
F1000Res. 2025 Jan 17;13:96. doi: 10.12688/f1000research.145845.2. eCollection 2024.
This study used ChatGPT for sentiment analysis to investigate the possible links between online sentiments and COVID-19 vaccination rates. It also examines Internet posts to understand the attitudes and reasons associated with vaccine-related opinions.
We collected 500,558 posts over 60 weeks from the Blind platform, mainly used by working individuals, and 854 relevant posts were analyzed. After excluding duplicates and irrelevant content, attitudes toward and reasons for vaccine opinions were studied through sentiment analysis. The study further correlated these categorized attitudes with the actual vaccination data.
The proportions of posts expressing positive, negative, and neutral attitudes toward COVID-19 vaccines were 5%, 83%, and 12%, respectively. The total post count showed a positive correlation with the vaccination rate, indicating a high correlation between the number of negative posts about the vaccine and the vaccination rate. Negative attitudes were predominantly associated with societal distrust and perceived oppression.
This study demonstrates the interplay between public perceptions of COVID-19 vaccines as expressed through social media and vaccination behavior. These correlations can serve as useful clues for devising effective vaccination strategies.
本研究使用ChatGPT进行情感分析，以调查在线情绪与新冠疫苗接种率之间的可能联系。它还检查互联网帖子，以了解与疫苗相关观点相关的态度和原因。
我们从主要供上班族使用的Blind平台上收集了60周内的500,558条帖子，并对854条相关帖子进行了分析。在排除重复和无关内容后，通过情感分析研究了对疫苗观点的态度和原因。该研究进一步将这些分类态度与实际接种数据相关联。
对新冠疫苗表达积极、消极和中性态度的帖子比例分别为5%、83%和12%。帖子总数与接种率呈正相关，表明关于疫苗的负面帖子数量与接种率之间存在高度相关性。负面态度主要与社会不信任和感知到的压迫有关。
本研究证明了通过社交媒体表达的公众对新冠疫苗的看法与接种行为之间的相互作用。这些相关性可为制定有效的疫苗接种策略提供有用线索。
