Mori Yoshiro, Miyatake Nobuyuki, Suzuki Hiromi, Mori Yuka, Okada Setsuo, Tanimoto Kiyotaka
Department of Hygiene, Faculty of Medicine, Kagawa University, Miki 761-0793, Japan.
Sakaide City Hospital, Sakaide 762-8550, Japan.
Vaccines (Basel). 2023 Aug 5;11(8):1327. doi: 10.3390/vaccines11081327.
The aim of this study was to compare impressions of COVID-19 vaccination and influenza vaccination in Japan by analyzing social media (Twitter) using a text-mining method. We obtained 10,000 tweets using the keywords "corona vaccine" and "influenza vaccine" on 15 December 2022 and 19 February 2023. We then counted the number of times the words were used and listed frequency of these words by a text-mining method called KH Coder. We also investigated concepts in the data using groups of words that often appeared together or groups of documents that contained the same words using multi-dimensional scaling (MDS). "Death" in relation to corona vaccine and "severe disease" for influenza vaccine were frequently used on 15 December 2022. The number of times the word "death" was used decreased, "after effect" was newly recognized for corona vaccine, and "severe disease" was not used in relation to influenza vaccine. Through this comprehensive analysis of social media data, we observed distinct variations in public perceptions of corona vaccination and influenza vaccination in Japan. These findings provide valuable insights for public health authorities and policymakers to better understand public sentiment and tailor their communication strategies accordingly.
本研究的目的是通过使用文本挖掘方法分析社交媒体(推特),比较日本民众对新冠疫苗接种和流感疫苗接种的看法。我们在2022年12月15日和2023年2月19日使用关键词“新冠疫苗”和“流感疫苗”获取了10000条推文。然后,我们通过一种名为KH Coder的文本挖掘方法统计了这些词汇的使用次数,并列出了它们的出现频率。我们还使用多维缩放(MDS),通过经常一起出现的词汇组或包含相同词汇的文档组来研究数据中的概念。2022年12月15日,与新冠疫苗相关的“死亡”以及与流感疫苗相关的“重症疾病”被频繁提及。“死亡”一词的使用次数减少,新冠疫苗新出现了“后遗症”的说法,而与流感疫苗相关的“重症疾病”则未被提及。通过对社交媒体数据的全面分析,我们观察到日本民众对新冠疫苗接种和流感疫苗接种的看法存在明显差异。这些发现为公共卫生当局和政策制定者提供了宝贵的见解,有助于他们更好地了解公众情绪,并据此调整沟通策略。