2020 年 31 巻 p. 1-8
Social media has been utilized by health organizations as a tool to disseminate health related information, and as a platform for users to voice out their sentiments or opinions. Coronavirus disease COVID-19 has continued to greatly impact the lives of people around the world. This paper aims to discover hidden topics, sub-topics, or themes within the corpus of tweets regarding the state of emergency in Japan due to the novel coronavirus by conducting a quantitative analysis of text data mined from Twitter. Three distinct clusters of words which represent sub-topics or themes were identified from thousands of tweets containing the keyword “state of emergency”. These are concerns regarding the closure of business establishments and the cancellation of events, gift promotion plan strategies, and concerns regarding the effects of the declaration of the state of emergency. Discovering insights hidden in tweets using the approach described in this study is an effective way of monitoring and gauging public opinion which leads to the creation of novel strategies as well as the evaluation of existing or current strategies.