Judith Borghouts, Yicong Huang, Suellen Hopfer, Chen Li, Gloria Mark
{"title":"Wording Matters: the Effect of Linguistic Characteristics and Political Ideology on Resharing of COVID-19 Vaccine Tweets","authors":"Judith Borghouts, Yicong Huang, Suellen Hopfer, Chen Li, Gloria Mark","doi":"10.1145/3637876","DOIUrl":null,"url":null,"abstract":"<p>Social media platforms are frequently used to share information and opinions around vaccinations. The more often a message is reshared, the wider the reach of the message and potential influence it may have on shaping people’s opinions to get vaccinated or not. We used a negative binomial regression to investigate whether a message’s linguistic characteristics (degree of concreteness, emotional arousal, and sentiment) and user characteristics (political ideology and number of followers) may influence users’ decisions to reshare tweets related to the COVID-19 vaccine. We analyzed US English-language tweets related to the COVID-19 vaccine between May 2020 and October 2021 (N = 236,054). </p><p>Tweets with positive and high-arousal words were more often retweeted than negative, low-arousal tweets. Tweets with abstract words were more often retweeted than tweets with concrete words. In addition, while Liberal users were more likely to have tweets with a positive sentiment reshared, Conservative users were more likely to have tweets with a negative sentiment reshared. Our results can inform public health messaging on how to best phrase vaccine information to impact engagement and information resharing, and potentially persuade a wider set of people to get vaccinated.</p>","PeriodicalId":50917,"journal":{"name":"ACM Transactions on Computer-Human Interaction","volume":"85 1","pages":""},"PeriodicalIF":4.8000,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Computer-Human Interaction","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3637876","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
引用次数: 0
Abstract
Social media platforms are frequently used to share information and opinions around vaccinations. The more often a message is reshared, the wider the reach of the message and potential influence it may have on shaping people’s opinions to get vaccinated or not. We used a negative binomial regression to investigate whether a message’s linguistic characteristics (degree of concreteness, emotional arousal, and sentiment) and user characteristics (political ideology and number of followers) may influence users’ decisions to reshare tweets related to the COVID-19 vaccine. We analyzed US English-language tweets related to the COVID-19 vaccine between May 2020 and October 2021 (N = 236,054).
Tweets with positive and high-arousal words were more often retweeted than negative, low-arousal tweets. Tweets with abstract words were more often retweeted than tweets with concrete words. In addition, while Liberal users were more likely to have tweets with a positive sentiment reshared, Conservative users were more likely to have tweets with a negative sentiment reshared. Our results can inform public health messaging on how to best phrase vaccine information to impact engagement and information resharing, and potentially persuade a wider set of people to get vaccinated.
期刊介绍:
This ACM Transaction seeks to be the premier archival journal in the multidisciplinary field of human-computer interaction. Since its first issue in March 1994, it has presented work of the highest scientific quality that contributes to the practice in the present and future. The primary emphasis is on results of broad application, but the journal considers original work focused on specific domains, on special requirements, on ethical issues -- the full range of design, development, and use of interactive systems.