Using the immediate release of the Working Group 1 Summary for Policymakers of the Intergovernmental Panel on Climate Change Fifth Assessment Report as a case study, this article seeks to describe what type of actors were most active during the summary release, the substance of the most propagated tweets during the summary release, and the media sources that attracted the most attention during the summary release. The results from the study suggest that non-elite actors, such as individual bloggers and concerned citizens, accounted for the majority of the most propagated tweets in the sample. This study also finds that the majority of the most propagated tweets in the sample focused on public understanding of the report. Finally, while mainstream media sources were the most frequently discussed media sources, a number of new media and science news and information sources compete for audience attention.

According to cultural cognition theory, individuals hold opinions about politically contested issues like climate change that are consistent with their “cultural way of life,” conforming their opinions to how they think society should be organized and to what they perceive are the attitudes of their cultural peers. Yet despite dozens of cultural cognition studies, none have directly examined the role of the news media in facilitating these differential interpretations. To address this gap, drawing on a national survey of US adults administered in 2015, we statistically modeled the cultural cognition process in relation to news choices and media effects on public attitudes about climate change. Individuals possessing strongly held cultural worldviews, our findings show, not only choose news outlets where they expect to find culturally congruent arguments about climate change, but they also selectively process the arguments they encounter. Overall, our study demonstrates the substantial role that cultural cognition in combination with news media choices play in contributing to opinion polarization on climate change and other politicized science topics.

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We have little systematic knowledge about scholars’ goals for public engagement in the academic literature. This study therefore provides a secondary analysis of two surveys of scholars that included closed-ended questions about goals. One survey from 2017 was from a sample of Canadian grant recipients from a federal science funding agency, while the second survey from 2018 comes from a sample of professors at top American research universities. The focus of this research is on both presenting novel data about scholars’ expressed goals and exploring the relationships between these goals and potential predictors of these goals, including demographics, past engagement behavior, and overall views about public engagement. Areas for future research are then described.

This article investigates the impact science communication training has on engagement intentions through a parallel multiple mediation model. Theory of planned behavior variables for internal efficacy, response efficacy, norms, and attitudes are examined as potential mediators. Based on a survey of randomly selected scientists from universities in the Association of American Universities, results indicate indirect effects for internal efficacy and attitudes toward the audience and consistent direct effects found in earlier research. This research provides a more comprehensive examination of how communication training contributes to scientists’ public engagement activity.

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The use of artificial intelligence-based algorithms for the curation of news content by social media platforms like Facebook and Twitter has upended the gatekeeping role long held by traditional news outlets. This has caused some US policymakers to argue that platforms are skewing news diets against them, and such claims are beginning to take hold among some voters. In a nationally representative survey experiment, we explore whether traditional models of media bias perceptions extend to beliefs about algorithmic news bias. We find that partisan cues effectively shape individuals’ attitudes about algorithmic news bias but have asymmetrical effects. Specifically, whereas in-group directional partisan cues stimulate bias perceptions for members of both parties, Democrats, but not Republicans, also respond to out-group cues. We conclude with a discussion about the implications for the formation of attitudes about new technologies and the potential for polarization.

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