Framing Disinformation and Misinformation in Media: Impacts on Public Discourse

• In Event: The Spread and Correction of Misinformation and Disinformation

Abstract

The rise of social media has led to concerns about spreading false information and its potential impacts on public discourse (Lewandowsky et al., 2017; Pérez-Escolar et al., 2023). With the importance of mass media coverage in informing the public about the issue, existing research has examined partisan differences in fake news coverage (Che et al., 2018), representation of misinformation and fact-checking in COVID-19 coverage (Maloney et al., 2024), and gatekeeping of fake news discourses by media versus social media (Al-Rawi, 2019). Recent work has also begun analyzing news media coverage of fake news itself (Cheng, 2023).

However, previous studies have also been limited in scope, focusing on narrow events or timeframes, single media sources, or not differentiating types of false information. This study helps fill this gap through large-scale computational analysis of print and digital media coverage referencing disinformation, misinformation, propaganda, and fake news over two decades.

Theoretically, this study is rooted in media framing and agenda-setting (Scheufele, 1999). Traditional and social media can potentially wield significant agenda-setting power and framing effects, especially with fake news (Vargo et al., 2018). The importance of this coverage is also underscored by its specific varied potential impact on public opinion, from legitimate concerns promoting critical thinking and awareness to the dangers of misinformation, to unintentionally increasing mistrust in legitimate ‘real’ news (Newman et al., 2022).

Methodologically, this study uses a computational mixed-method approach to analyze large-scale print and digital media coverage and investigate trends in framing, rhetorical techniques, and shifts in public discourse surrounding mis- and dis-information. The data was collected using a comprehensive set of search terms, including “disinformation,” “misinformation,” “propaganda,” and “fake news”. Data was retrieved from the 25 highest-circulation U.S. newspapers over two decades (2000-2023) and includes 132,256 articles. It is then analyzed using a mixed-methods approach, including automated tools (specifically, a topic-model network approach, Walter & Ophir, 2019) as well as qualitative and rhetorical analysis of items of interest highlighted by the automated approach.

The threat of mis- and disinformation has grown in recent decades (Lewandowsky et al., 2017). While ample attention has been paid to its nature, effects, and correction, relatively little attention has been paid to how this threat is being communicated to the public via the media. To address this lacuna, this study analyzes a unique dataset, comprehensive in terms of keywords and timespan (2000-2023). Its findings would provide insights into the media’s role in combatting or exacerbating the “dark side” of ubiquitous digital and print media, with implications for journalism practice and policy responses, to mitigate democratic backsliding exacerbated by the spread of misinformation while avoiding the deleterious effects of such coverage.

References

Al-Rawi, A. (2019). Gatekeeping fake news discourses on mainstream media versus social media. Social science computer review, 37(6), 687-704.

Che, X., Metaxa-Kakavouli, D., & Hancock, J. T. (2018, October). Fake News in the News: An Analysis of Partisan Coverage of the Fake News Phenomenon. In Companion of the 2018 ACM Conference on Computer Supported Cooperative Work and Social Computing (pp. 289-292).

Cheng, J. W. (2023). News on Fake News: The Framing of Fake News in News on Fake News: The Framing of Fake News in. Journal of Information and Communication Research, 40(4), 67-87.

Lewandowsky, S., Ecker, U. K., & Cook, J. (2017). Beyond Misinformation: Understanding and Coping with the “Post-Truth” Era. Journal of Applied Research in Memory and Cognition, 6(4), 353-369.

Maloney, E. K., White, A. J., Samuel, L., Boehm, M., & Bleakley, A. (2024). COVID-19 coverage from six network and cable news sources in the United States: Representation of misinformation, correction, and portrayals of severity. Public Understanding of Science, 33(1), 58-72.

Newman, N., Fletcher, R., Schulz, A., Andi, S., Robertson, C. T., & Nielsen, R. K. (2022). Reuters Institute digital news report 2022. Reuters Institute.

Pérez-Escolar, M., Lilleker, D., & Tapia-Frade, A. (2023). A systematic literature review of the phenomenon of disinformation and misinformation. Media and Communication, 11(2), 76-87.

Scheufele, D. A. (1999). Framing as a theory of media effects. Journal of communication, 49(1), 103-122.

Vargo, C. J., Guo, L., & Amazeen, M. A. (2018). The agenda-setting power of fake news: A big data analysis of the online media landscape from 2014 to 2016. New Media & Society, 20(5), 2028-2049.

Walter, D., & Ophir, Y. (2019). News Frame Analysis: An Inductive Mixed-Method Computational Approach. Communication Methods and Measures, 13(4), 248-266.

Authors

• Sonny Patel, Georgia State University

• Dror Walter, Georgia State University