Focusing on a polarized issue—U.S. gun violence—this study examines agenda setting as an antecedent of political expression on social media. A state-of-the-art machine-learning model was used to analyze news coverage from 25 media outlets—mainstream and partisan. Those results were paired with a two-wave panel survey conducted during the 2018 U.S. midterm elections. Findings show mainstream media shape public opinion about gun violence, which then stimulates expression about the issue on social media. The study also reveals that partisan media’s gun violence coverage has significant cross-cutting effects. Notably, exposure to conservative media will decrease public salience of gun violence, pivot opinion in a more conservative direction, and discourage social media expression; and all of these effects are stronger among liberals.
more » « less- PAR ID:
- 10403843
- Publisher / Repository:
- SAGE Publications
- Date Published:
- Journal Name:
- Communication Research
- Volume:
- 51
- Issue:
- 8
- ISSN:
- 0093-6502
- Format(s):
- Medium: X Size: p. 1033-1057
- Size(s):
- p. 1033-1057
- Sponsoring Org:
- National Science Foundation
More Like this
-
null (Ed.)Different news articles about the same topic often offer a variety of perspectives: an article written about gun violence might emphasize gun control, while another might promote 2nd Amendment rights, and yet a third might focus on mental health issues. In communication research, these different perspectives are known as “frames”, which, when used in news media will influence the opinion of their readers in multiple ways. In this paper, we present a method for effectively detecting frames in news headlines. Our training and performance evaluation is based on a new dataset of news headlines related to the issue of gun violence in the United States. This Gun Violence Frame Corpus (GVFC) was curated and annotated by journalism and communication experts. Our proposed approach sets a new state-of-the-art performance for multiclass news frame detection, significantly outperforming a recent baseline by 35.9% absolute difference in accuracy. We apply our frame detection approach in a large scale study of 88k news headlines about the coverage of gun violence in the U.S. between 2016 and 2018.more » « less
-
Abstract We propose a new way of imagining and measuring opinions emerging from social media. As people tend to connect with like-minded others and express opinions in response to current events on social media, social media public opinion is naturally occurring, temporally sensitive, and inherently social. Our framework for measuring social media public opinion first samples targeted nodes from a large social graph and identifies homogeneous, interactive, and stable networks of actors, which we call “flocks,” based on social network structure, and then measures and presents opinions of flocks. We apply this framework to Twitter and provide empirical evidence for flocks being meaningful units of analysis and flock membership predicting opinion expression. Through contextualizing social media public opinion by foregrounding the various homogeneous networks it is embedded in, we highlight the need to go beyond the aggregate-level measurement of social media public opinion and study the social dynamics of opinion expression using social media.
-
Public opinion is shaped by the information news media provide, and that information in turn may be shaped by the ideological preferences of media outlets. But while much attention has been devoted to media bias via overt ideological language or topic selection, a more unobtrusive way in which the media shape opinion is via the strategic inclusion or omission of partisan events that may support one side or the other. We develop a latent variable-based framework to predict the ideology of news articles by comparing multiple articles on the same story and identifying partisan events whose inclusion or omission reveals ideology. Our experiments first validate the existence of partisan event selection, and then show that article alignment and cross-document comparison detect partisan events and article ideology better than competitive baselines. Our results reveal the high-level form of media bias, which is present even among mainstream media with strong norms of objectivity and nonpartisanship. Our codebase and dataset are available at https://github.com/launchnlp/ATC.more » « less
-
Abstract Gun violence is a major public health problem and costs the United States $280 billion annually (1). Although adolescents are disproportionately impacted (e.g. premature death), we know little about how close adolescents live to deadly gun violence incidents and whether such proximity impacts their socioemotional development (2, 3). Moreover, gun violence is likely to shape youth developmental outcomes through biological processes—including functional connectivity within regions of the brain that support emotion processing, salience detection, and physiological stress responses—though little work has examined this hypothesis. Lastly, it is unclear if strong neighborhood social ties can buffer youth from the neurobehavioral effects of gun violence. Within a nationwide birth cohort of 3,444 youth (56% Black, 24% Hispanic) born in large US cities, every additional deadly gun violence incident that occurred within 500 meters of home in the prior year was associated with an increase in behavioral problems by 9.6%, even after accounting for area-level crime and socioeconomic resources. Incidents that occurred closer to a child's home exerted larger effects, and stronger neighborhood social ties offset these associations. In a neuroimaging subsample (N = 164) of the larger cohort, living near more incidents of gun violence and reporting weaker neighborhood social ties were associated with weaker amygdala–prefrontal functional connectivity during socioemotional processing, a pattern previously linked to less effective emotion regulation. Results provide spatially sensitive evidence for gun violence effects on adolescent behavior, a potential mechanism through which risk is biologically embedded, and ways in which positive community factors offset ecological risk.
-
Abstract When an individual or group trauma becomes a shared public experience through widespread media coverage (e.g., mass violence, being publicly outed), sharing a social identity with a targeted individual or group of victims may amplify feelings of personal vulnerability. This heightened perceived threat may draw people to engage with trauma-related media because of increased vigilance for self-relevant threats, which can, in turn, amplify distress. We studied this possibility among two U.S. national samples following the 2016 Pulse nightclub massacre in Orlando, FL (N = 4675) and the 2018 Dr. Christine Blasey Ford and Judge Brett Kavanaugh Supreme Court Senate hearings (N = 4894). Participants who shared LGBT or Hispanic identities with Pulse massacre victims reported greater exposure to massacre-related media and acute stress. Participants who shared Dr. Blasey Ford’s identities as a victim of interpersonal violence and a Democrat reported more hearings-related media exposure and acute stress. Indirect effects of shared single identity on acute stress through self-reported event-related media exposure emerged in both studies. Results for sharing dual identities with victims were mixed. These findings have implications for media use and public health.