In a rapidly changing public health crisis such as COVID-19, researchers need innovative approaches that can effectively link qualitative approaches and computational methods. In this article, computational and qualitative methods are used to analyze survey data collected in March 2020 ( n = 2,270) to explore the content of persuasive messages and their relationship with self-reported health behavior—that is, social distancing. Results suggest that persuasive messages, based on participants’ perspectives, vary by gender and race and are associated with self-reported health behavior. This article illustrates how qualitative analysis and structural topic modeling can be used in synergy in a public health study to understand the public’s perception and behavior related to science issues. Implications for health communication and future research are discussed.

Understanding how individuals perceive the barriers and benefits of precautionary actions is key for effective communication about public health crises, such as the COVID-19 outbreak. This study used innovative computational methods to analyze 30,000 open-ended responses from a large-scale survey to track how Wisconsin (U.S.A.) residents' perceptions of the benefits of and barriers to performing social distancing evolved over a critical time period (March 19th to April 1st, 2020). Initially, the main barrier was practical related, however, individuals later perceived more multifaceted barriers to social distancing. Communication about COVID-19 should be dynamic and evolve to address people's experiences and needs overtime.

We examined initial newspaper coverage of the COVID-19 outbreak (January–May 2020) in the United States and China, countries with contrasting media systems and pandemic experiences. We join the context-rich media systems literature and the longitudinal nature of the issue-attention literature to expand each by providing more system-level context for explaining how media cover an issue over time. U.S. coverage peaked later and stayed consistently high, while Chinese coverage was more variable. The most prominent topics in Chinese coverage were related to domestic outbreak response, while U.S. coverage focused on politics, highlighting how issue-attention cycles differ across countries.

Misinformation and intergroup bias are two pathologies challenging informed citizenship. This article examines how identity language is used in misinformation and debunking messages about controversial science on the Chinese digital public spheres and their impact on how the public engage with science. We collected an 8-year time series dataset of public discussion ( N = 6,039) on one of the most controversial science issues in China (GMO) from a popular Q&A platform, Zhihu. We found that both misinformation and debunking messages use a substantial amount of group identity languages when discussing the controversial science issue, which we define as science factionalism—discussion about science is divided by factions that are formed upon science attitudes. We found that posts that use science factionalism receive more digital votes and comments, even among the science-savvy community in China. Science factionalism also increases the use of negativity in public discourse. We discussed the implications of how science factionalism interacts with the digital attention economy to affect public engagement with science misinformation.

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Public discourse and deliberation are key to developing socially responsible and acceptable human gene editing research and applications. Researchers have raised concerns, however, that discourse about heritable gene edits, especially for non-therapeutic (or enhancement) purposes, might negatively bias public opinion of applications, including non-heritable edits to cure or prevent disease. Yet limited research exists examining how information about different gene editing applications elicits different perceptions of the technology. Using a U.S.-representative sample and survey-embedded experiment, we tested how exposure to information about different types of edits affects support and perceptions of benefits, risks, and moral acceptability of human gene editing. We randomly assigned respondents to a control or to an experimental condition in which they read information about one of four broad types of potential applications: (1) heritable edits for enhancement; (2) heritable edits for therapy; (3) non-heritable edits for enhancement; (4) non-heritable edits for therapy. Respondents then answered questions tapping multiple dimensions of support for and risk/benefit perceptions of human gene editing. Our results indicate partial evidence that exposure to information about heritable and/or enhancement edits colors perceptions of human gene editing more broadly but also that support for therapeutic edits is robust. Participants who read information about therapy edits perceived human gene editing in general more favorably in terms of benefits, risks, and moral acceptability than did participants who read about enhancements. Exposure to information about therapy versus enhancement edits, however, did not significantly influence support for therapy edits in particular. Heritability of edits had significant influence only on perceived risk, with heritable edits triggering higher risk perceptions. Interestingly, heritability seems to primarily affect views of risk of gene editing but not views of benefits, moral acceptability, or levels of support. We did not find differing effects depending on whether heritable edits were for therapy or enhancement.