Going Beyond Affective Polarization: How Emotions and Identities are Used in Anti-Vaccination TikTok Videos

ABSTRACTThe rise of social media as a source of science and health information has brought challenges to informed citizenship and social trust due to the spread of misinformation, particularly anti-vaccination messages that incite hatred and discourage necessary health precautions. These messages often employ emotional appeals and identity cues. However, scholarship examining emotional appeals and identity cues in anti-vax messages is still at the nascent stage. Furthermore, most literature on emotions and identities on social media has focused on text-based platforms, despite the increasing popularity of interactive, multimodal platforms. To address these gaps, our paper analyzes recent TikTok anti-vax videos and incorporates the framework of multimodal frame processing, emotion-as-frames model, affective intelligence theory, and social identity theory. Our paper uncovers how different message modalities affect the impact of emotional narratives and identity cues on user engagement. We also investigate sociopolitical identity cues beyond partisan identities, expanding the current terrain of political communication. Our results demonstrate that audiences engage with emotional and identity cues in anti-vax videos differently based on distinct message modalities. We also found that identity cues related to interpersonal relationships (e.g. parental) and conspiracy groups were prevalent, in addition to partisan identity cues. These results offer new insights into sociopolitical identities beyond partisanship and highlight the importance of considering the multi-modal nature of video platforms. Overall, our paper sheds light on the complex relationship between emotions, identities, and message modalities on social media and provides important implications for addressing misinformation and improving science communication on digital platforms.KEYWORDS: Emotionidentitymultimodalityanti-vaxTikTokcomputational social science Disclosure StatementNo potential conflict of interest was reported by the author(s).Supplementary MaterialSupplemental data for this article can be accessed on the publisher's website at https://doi.org/10.1080/10584609.2023.2243852Data Availability StatementOur anonymized dataset and the analysis scripts are deposited at https://doi.org/10.7910/DVN/U6FIQW. We also included an instruction Read Me document about how to reproduce our findings.Open scholarshipThis article has earned the Center for Open Science badge for Open Data. The data are openly accessible at re3data.orgAdditional informationNotes on contributorsSang Jung KimSang Jung Kim is an Assistant Professor at the School of Journalism and Mass Communication from the University of Iowa. https://sangjungkim.comIsabel Iruani VillanuevaIsabel Iruani Villanueva is a PhD student at the Department of LIfe Sciences Communication from Unviersity of Wisconsin-Madison.Kaiping ChenKaiping Chen is an Assistant Professor at the Department of Life Sciences Communication from University of Wisconsin-Madison. For comments and questions, please email them to: kchen67@wisc.edu. https://www.kaipingchen.com