Purpose In recent years, the social impact of misinformation has intensified. The purpose of this study is to clarify the mechanism by which misinformation spreads in society. Design/methodology/approach Testing the following two hypotheses by a logit model analysis of survey data using actual fact-checked COVID-19 vaccine and political misinformation: people who believe that some misinformation is true are more likely to spread it than those who do not believe in its truthfulness; people with lower media and information literacy are more likely to spread misinformation than people with higher media and information literacy. Findings The two hypotheses are supported, and the trend was generally robust regardless of the method, whether the means of diffusion was social media or direct conversation. Social implications The authors derived the following four implications from the results: governments need to further promote media information literacy education; platform service providers should consider mechanisms to facilitate the spread and display of posts by people who are aware of misinformation; fact-checking should be further promoted; people should acquire information based on the assumption that people who believe in some misinformation tend to spread it more. Originality/value First, it quantitatively clarifies the relationship between misinformation, true/false judgements and dissemination behaviour. Second, it quantitatively clarifies the relationship between literacy and misinformation dissemination behaviour. Third, it conducts a comprehensive analysis of diffusion behaviours, including those outside of social media.

Purpose This study aims to reveal how the COVID-19 vaccine was accepted in the Japanese Twitter-sphere. This study explores how the topics related to the vaccine promotion project changed on Twitter and how the topics that were likely to spread changed during the vaccine promotion project. Design/methodology/approach The computational social science methodology was adopted. This study collected all tweets containing the word “vaccine” using the Twitter API from March to October 2021 and conducted the following analysis: analyzing frequent words and identifying topics likely to spread through the cosine similarity and Tobit model. Findings First, vaccine hesitancy–related words were frequently mentioned during the vaccine introduction and dissemination periods and had diffusing power only during the former period. Second, vaccine administration–related words were frequently mentioned and diffused through April to May and had diffusing power throughout the period. The background to these findings is that the sentiment of longing for vaccines outweighed that of hesitancy toward vaccines during this period. Originality/value This study finds that the timing of the rise in vaccine hesitation sentiment and the timing of the start of vaccine supply were misaligned. This is one of the reasons that Japan, which originally exhibited strong vaccine hesitancy, did not face vaccine hesitancy in the COVID-19 vaccine promotion project.

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This study investigates the bias of Twitter as an agenda-setter during COVID-19. Specifically, we analyze the agenda-setting function of Twitter (Study 1) and characteristics of information disseminators on Twitter, agenda-builders (Study 2), related to the COVID-19 pandemic. In Study 1, we examined rank correlations between the media agendas on COVID-19 and public agendas. The results indicated that Twitter agendas resonate with those who have liberal tendencies. In Study 2, we used data from the Internet survey to identify the political attitudes of agenda-builders who tweet or retweet on COVID-19. The results of the model analyses indicated that people with liberal tendencies, motivated by their political attitude, created original tweets, and some of those tweets were then retweeted by flaming-oriented people driven by a sense of justice. This seems to be how information about COVID-19 spreads on Twitter in Japan.