According to the World Health Organization (WHO), we are entering an age of “infodemics,” with misinformation leading to mistrust in health authorities, increasing risk-taking behaviors, and undermining public health responses (WHO 2020). While concerns are rapidly growing about the prevalence and harmful impact of health misinformation (Nan, Wang, and Thier 2021), scholars have not clearly defined health misinformation or its components. Without a clear definition and shared agreement on what constitutes health misinformation, comparisons across studies purportedly about health misinformation will remain challenging, hampering our efforts to understand this phenomenon, assess its effects, and design effective interventions. However, defining misinformation in the first place is exceedingly difficult, partly because the benchmarks we often use to diagnose misinformation (e.g., scientific evidence, expert consensus) are sometimes moving targets (Vraga and Bode 2020). In light of the ongoing debate about the nature of misinformation and the urgent need for a clear definition of health misinformation, this chapter aims to critically review current definitions of health misinformation, identify key challenges in defining health misinformation, and finally propose a tentative, unifying definition of health misinformation to guide future research. We conclude by discussing directions for future efforts in refining the definition for health misinformation.

Wang, Y., Thier, K., & Nan, X. (2022). Defining health misinformation. In A. Keselman, C. A. Smith & A. Wilson (Eds.), Combating Online Health Misinformation: A Professional’s Guide to Helping the Public (pp.3-16). Rowman & Littlefield.

Wang, Y., & Chen, Y. (2022). Characterizing discourses about COVID-19 vaccines on Twitter: a topic modeling and sentiment analysis approach. Journal of Communication in Healthcare, 1-10. https://doi.org/10.1080/17538068.2022.2054196

Evidence-based health communication is crucial for facilitating vaccine-related knowledge and addressing vaccine hesitancy. To that end, it is important to understand the discourses about COVID-19 vaccination and attend to the publics’ emotions underlying those discourses. We collect tweets related to COVID-19 vaccines from March 2020 to March 2021. In total, 304,292 tweets from 134,015 users are collected. We conduct a Latent Dirichlet Allocation (LDA) modeling analysis and a sentiment analysis to analyze the discourse themes and sentiments. This study identifies seven themes of COVID-19 vaccine-related discourses. Vaccine advocacy (24.82%) is the most widely discussed topic about COVID-19 vaccines, followed by vaccine hesitancy (22.29%), vaccine rollout (12.99%), vaccine facts (12.61%), recognition for healthcare workers (12.47%), vaccine side effects (10.07%), and vaccine policies (4.75%). Trust is the most salient emotion associated with COVID-19 vaccine discourses, followed by anticipation, fear, joy, sadness, anger, surprise, and disgust. Among the seven topics, vaccine advocacy tweets are most likely to receive likes and comments, and vaccine fact tweets are most likely to receive retweets. When talking about vaccines, publics’ emotions are dominated by trust and anticipation, yet mixed with fear and sadness. Although tweets about vaccine hesitancy are prevalent on Twitter, those messages receive fewer likes and comments than vaccine advocacy messages. Over time, tweets about vaccine advocacy and vaccine facts become more dominant whereas tweets about vaccine hesitancy become less dominant among COVID-19 vaccine discourses, suggesting that publics become more confident about COVID-19 vaccines as they obtain more information.