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Trust in scientific actors and institutions in the United States is at an all-time low. At the same time, studies show that people use social media for science information and become increasingly vulnerable to COVID-19-related misinformation. Yet, we do not know whether low levels of trust cause people to turn to social media in the first place. We argue that if people do not trust the scientific information provided by scientists, they are likely to turn to social media to get alternative scientific information (rather than relying on mainstream sources to get pandemic-related information), which in turn can increase susceptibility to COVID-19 misperceptions. Based on two-wave U.S. panel data, we found that distrust in science drives the uses of social media for COVID-19 information, and reliance on social media for COVID-19 information increases susceptibility to COVID-19 misperceptions. [ABSTRACT FROM AUTHOR]

The literature on misinformation has not provided sufficient empirical evidence concerning its political consequences. To amend this trend, this study examines how widespread misinformation on social media elevates political cynicism, which has peaked over the past decade in the United States. Using two-wave survey data collected both before and after the 2020 US presidential election, we present evidence that social media use triggers political cynicism, which is mediated through exposure to misinformation. In addition, the results reveal that the mediating relationship only holds among nonpartisans. Implications for democracy are also discussed. [ABSTRACT FROM AUTHOR]

Although collective efforts are essential to fight COVID-19, public opinion in the United States is sharply divided by partisan attitudes and health beliefs. Addressing the concern that media use facilitates polarization, this study investigated whether social and traditional media use for COVID-19 information attenuates or reinforces existing disparities. This article focuses on two important areas where the public is highly polarized: partisan affect and vaccine attitudes. Contradicting the filter bubble claim, our survey (n = 1106) revealed that social media use made people less polarized in both partisan affect and vaccine hesitancy. In contrast, traditional media use made people more polarized in partisan affect. These findings corroborate the growing evidence that social media provide diverse viewpoints and incidental learning. [ABSTRACT FROM AUTHOR]

Upon a surge of misinformation surrounding COVID-19, fact-checking has received much attention as a tool to fight the rampant misinformation. However, such correction efforts have faced challenges from partisans' biased information processing. For example, partisans trust or distrust a fact-checking message based on whether the message benefits or harms their supporting party. To minimize such politically biased processing of corrective health information, this experimental study examined how different source labels of fact-checkers (human experts vs. AI vs. user consensus) affect partisans' perceived credibility of fact-checking messages about COVID-19. Our findings showed that AI and user consensus (vs. human experts) source labels on fact-checking messages significantly reduced partisan-based motivated reasoning in evaluating fact-checking message credibility. [ABSTRACT FROM AUTHOR]

AI can make mistakes and cause unfavorable consequences. It is important to know how people react to such AI-driven negative consequences and subsequently evaluate the fairness of AI's decisions. This study theorizes and empirically tests two psychological mechanisms that explain the process: (a) heuristic expectations of AI's consistent performance (automation bias) and subsequent frustration of unfulfilled expectations (algorithmic aversion) and (b) heuristic perceptions of AI's controllability over negative results. Our findings from two experimental studies reveal that these two mechanisms work in an opposite direction. First, participants tend to display more sensitive responses to AI's inconsistent performance and thus make more punitive assessments of AI's decision fairness, when compared to responses to human experts. Second, as participants perceive AI has less control over unfavorable outcomes than human experts, they are more tolerant in their assessments of AI. [ABSTRACT FROM AUTHOR]

Upon the growing concern over a massive infodemic and politicization of health issues during the COVID-19 pandemic, this study investigated how individuals' use of partisan media and Trump briefings, along with other information sources, predicts risk preventive behaviors. Drawing on the Extended Parallel Process Model (EPPM), our survey analysis (n= 1,106) revealed that those obtaining COVID-19 information from conservative media and Trump briefings were less likely to believe that COVID-19 is a serious threat (perceived threat) and that recommended preventive behaviors are effective and feasible (perceived efficacy). These beliefs, in turn, resulted in their decreased intentions to adopt risk preventative behaviors. In contrast, those who got COVID-19 information from liberal media, health organizations' briefings, and traditional media reported heightened threat and efficacy perception, which, in turn, led to their willingness to take risk preventive actions. [ABSTRACT FROM AUTHOR]

One critical lesson learned from public opinion research about climate change is that the cost of politicization is disastrous. Although the literature has shown the dire consequences of politicized science issues, few have examined how such politicization is possibly triggered by political leaders in a seemingly nonpartisan science topic. Using two experiments (total n = 1,249), this article demonstrates how political cues over scientific expertise shape individuals' beliefs in the vaccine and autism debate. The results indicate that Republicans tend to follow President Trump compared to scientists in the subject matter. On the other hand, Democrats follow scientists but are not influenced by Trump. The implications of political encroachment into health and science are discussed. [ABSTRACT FROM AUTHOR]

Although selective avoidance, commonly practiced as unfriending and muting on social media, has been assumed to be at odds with the democratic ideal of deliberation, academic literature says little about its antecedents and consequences. Drawing from the framework of psychological needs for information processing, we examine whether need for cognition and need to evaluate interact to predict selective avoidance, which then facilitates political expression on social media. Analyses of a two-wave survey collected before and after the 2018 midterm election in the U.S. suggest that individuals with low need for cognition but high need to evaluate were relatively unlikely to engage in selective avoidance. However, the supposedly ideal type of citizens high on both needs tended to engage in selective avoidance intensively to further engage in political expression on social media. [ABSTRACT FROM AUTHOR]

Despite a fast-growing body of literature on fake news and mis-/disinformation, there remains surprisingly little empirical work on the social/political consequences of exposure to false information. Addressing this issue, this study provides initial evidence that perceptions of false information exposure catalyze political cynicism. The findings from a two-wave panel survey during the 2018 US midterm elections reveal that perceptions of false information exposure 2 weeks before the election significantly predict the changes in political cynicism immediately after the election day. We also find that social media news use in Wave 1 significantly relates to political cynicism in Wave 2 indirectly through perceptions of mis-/disinformation exposure. The autoregressive regression model indicates that our findings are robust after controlling for prior levels of cynicism. [ABSTRACT FROM AUTHOR]

Concerns over fake news have triggered a renewed interest in various forms of media literacy. Prevailing expectations posit that literacy interventions help audiences to be "inoculated" against any harmful effects of misleading information. This study empirically investigates such assumptions by assessing whether individuals with greater literacy (media, information, news, and digital literacies) are better at recognizing fake news, and which of these literacies are most relevant. The results reveal that information literacy—but not other literacies—significantly increases the likelihood of identifying fake news stories. Interpreting the results, we provide both conceptual and methodological explanations. Particularly, we raise questions about the self-reported competencies that are commonly used in literacy scales. [ABSTRACT FROM AUTHOR]

This study investigated whether increased technological affordances, characterized by the rise of social media, diversified communication in climate change discourse. Extending the literature of intermedia agenda setting, this study examined agenda and frame contagion across Twitter and online news media. Using a large dataset of media content about climate change, time-series analysis showed that news media played a major role in setting agendas and frames, but Twitter has increased its dominance in climate change discussions. The findings address both opportunities for strategic science communication and challenges resulting from unverified scientific claims (e.g., hoax frames) spread on social media. [ABSTRACT FROM AUTHOR]