Social Protests in the Trump Era: A Topic-Network Approach

• In Event: Truth Hurts: New Data, Old Problems in Political Communication Research

Abstract

The Trump presidency was accompanied by multiple social protests and organized marches, including the March for science, March for our lives, the Women’s march, and the Unite the Right rally. The Guardian went as far as describing our era a “golden age of protest”, indicating that “over the course of the first 15 months of the 45th presidency, more people have joined demonstrations than at any other time in American history“ (Kauffman, 2018). The ways protests and protesters are portrayed in the mass media can influence public opinion, support for the causes and even the approach taken by officials, such as police forces, toward the event (McFarlane & Hay, 2003).
More specifically, previous research suggested that the news framing of a social protest, the process by which journalists emphasize some aspects of an event while deemphasizing others (Entman, 1993), could contribute to its success or failure. Therefore, efforts have been made to identify dominant media frames used by journalists in the coverage of social protests and to examine their effects on audiences (Nelson & Oxley, 1999).
The Guardian aforementioned quote emphasizes the divisive role played by president Trump in bringing people to the streets, in light of the increased partisan polarization in the U.S (Andris et al., 2015). In this study we examine whether these political changes have influenced news media framing of social protests, examining the full coverage in the Washington Post, the New York Times, the Wall Street Journal, and USAToday, of four prominent demonstration that took place during Trump’s presidency, that focused on far-right agenda (Unite the right in Charlottesville, VA), gun control (March for our lives), women’s rights (Women’s march), and science and climate (March for science). The corpus consists of 2,780 articles.
To examine salient news frames over this large corpus, we use a novel computational inductive method for the identification of media frames, combining unsupervised machine learning and network analysis: the Analysis of Topic Model Networks, ANTMN (Walter & Ophir, 2019). In ANTMN, topics are operationalized as frame components, and clusters of topics found in a network analysis as complete frames (frame packages, see Van Gorp, 2010). Our analysis identified 40 topics, that were automatically clustered into three distinct media frames. Two of the frames correspond to prior research: one focusing on Law and Order, and another focusing on Free Speech and the substantive content of the protest. However, we find a third dominant frame that was not found in prior research on social protest, one focusing of president Trump, his reactions to protests, his divisive views on the topics protested (e.g., allegations of sexual assaults against him; his refusal to condemn neo-Nazis and other extremists after the tragic consequences of the Charlottesville march), his relationships with politicians and other elites (e.g., CEOs), and the ways protests affect his presidency and the Republican party in general (e.g., effects on midterm elections).
This emerging media frame could change the way audiences learn of and react to social protests. Such coverage risks deepening cultural divides along partisan lines, and alarmingly, increasing the possibility that social causes will be evaluated by the public through a lens of political personification, where the merits and dangers of social protests will be evaluated on the basis of their influence on an individual leader, in this case, the president of the United States.

References
Andris, C., Lee, D., Hamilton, M. J., Martino, M., Gunning, C. E., & Selden, J. A. (2015). The Rise of Partisanship and Super-Cooperators in the U.S. House of Representatives. PLOS ONE, 10(4), e0123507. https://doi.org/10.1371/journal.pone.0123507
Entman, R. M. (1993). Framing: Toward Clarification of a Fractured Paradigm. Journal of Communication, 43(4), 51–58. https://doi.org/10.1111/j.1460-2466.1993.tb01304.x
Kauffman, L. A. (2018). We are living through a golden age of protest. Retrieved from: https://www.theguardian.com/commentisfree/2018/may/06/protest-trump-direct-action-activism
McFarlane, T., & Hay, I. (2003). The battle for Seattle: Protest and popular geopolitics in The Australian newspaper. Political Geography, 22(2), 211–232. https://doi.org/10.1016/S0962-6298(02)00090-2
Nelson, T. E., & Oxley, Z. M. (1999). Issue Framing Effects on Belief Importance and Opinion. The Journal of Politics, 61(4), 1040–1067. https://doi.org/10.2307/2647553
van Gorp, B. (2010). Strategies to take subjectivity out of framing analysis. In P. D’Angelo & J. A. Kuypers (Eds.),Doing news framing analysis: Empirical and theoretical perspectives (pp. 100–125). New York, NY: Routledge.
Walter, D., & Ophir, Y. (2019). News Frame Analysis: An Inductive Mixed-method Computational Approach. Communication Methods and Measures, 1–19. https://doi.org/10.1080/19312458.2019.1639145

Authors

• Yotam Ophir, University at Buffalo

• Devin Khayri Forde, State University of New York at Buffalo

• Madison Neurohr, University at Buffalo

• Dror Walter, Georgia State University