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Using Twitter to Study Public Discourse in the Wake of Judicial Decisions

Public Reactions to the Supreme Court’s Same-Sex-Marriage Cases

Published online by Cambridge University Press:  21 October 2022

Tom S. Clark ,
Jeffrey K. Staton ,
Yu Wang  and
Eugene Agichtein
Tom S. Clark*
Affiliation:
Emory University
Jeffrey K. Staton
Affiliation:
Emory University
Yu Wang
Affiliation:
Emory University
Eugene Agichtein
Affiliation:
Emory University
*
Contact the corresponding author, Tom S. Clark, at [email protected].
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Abstract

At the intersection of behavioral and institutional studies of policy making lie a series of questions about how elite choices affect mass public opinion. Scholars have considered how judicial decisions—especially US Supreme Court decisions—affect individuals’ support for specific policy positions. These studies yield a series of competing findings. Whereas past research uses opinion surveys to assess how individuals’ opinions are shaped, we believe that modern techniques for analyzing social media provide analytic leverage that traditional approaches do not offer. We present a framework for employing Twitter data to study mass opinion discourse. We find that the Supreme Court’s decisions relating to same-sex marriage in 2013 had significant effects on how the public discussed same-sex marriage and had a polarizing effect on mass opinion. We conclude by connecting these findings and our analyses to larger problems and debates in the area of democratic deliberation and big-data analysis.

Type
Research Article
Information
Journal of Law and Courts , Volume 6 , Issue 1 , Spring 2018 , pp. 93 - 126
Copyright
© 2018 by the Law and Courts Organized Section of the American Political Science Association. All rights reserved.

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Footnotes

We thank Shana Gadarian, John Kastellec, Markus Prior, and Chris Zorn for helpful comments and suggestions. We thank Leeann Bass, Nate Edwards, Alicia Ju, and Ashley Moraguez for research assistance. Previous versions of this article were presented at the University of Mannheim, the 2014 meeting of the Midwest Political Science Association, the 2014 meeting of the European Consortium on Political Research, and the Second Annual Atlanta Computational Social Science Workshop.

References

Achen, Christopher H. 1975. “Mass Political Attitudes and the Survey Response.” American Political Science Review 69 (4): 1218–31.CrossRefGoogle Scholar
Allan, James, ed. 2002. Topic Detection and Tracking: Event-Based Information Organization. Boston: Springer.CrossRefGoogle Scholar
Banks, Antoine J., and Valentino, Nicholas A. 2012. “Emotional Substrates of White Racial Attitudes.” American Journal of Political Science 56 (2): 286–97.CrossRefGoogle Scholar
Barber, Benjamin. 1984. Strong Democracy: Participatory Politics for a New Age. Berkeley: University of California Press.Google Scholar
Barberá, Pablo. 2015. “Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data.” Political Analysis 23 (1): 76–91.CrossRefGoogle Scholar
Barberá, Pablo, and Rivero, Gonzalo. 2014. “Understanding the Political Representativeness of Twitter Users.” Social Science Computer Review 33 (6): 712–29.CrossRefGoogle Scholar
Barbosa, Luciano, and Feng, Junlan. 2010. “Robust Sentiment Detection on Twitter from Biased and Noisy Data.” In Proceedings of the 23rd International Conference on Computational Linguistics: Posters, 36–44. Stroudsburg, PA: Association for Computational Linguistics.Google Scholar
Baum, Lawrence. 2007. Judges and Their Audiences: A Perspective on Judicial Behavior. Princeton, NJ: Princeton University Press.Google Scholar
Berinsky, Adam J., Huber, Gregory A., and Lenz, Gabriel S. 2012. “Evaluating Online Labor Markets for Experimental Research: Amazon.com’s Mechanical Turk.” Political Analysis 20 (3): 351–68.CrossRefGoogle Scholar
Bermingham, Adam, and Smeaton, Alan F. 2012. “On Using Twitter to Monitor Political Sentiment and Predict Election Results.” In Proceedings of the Workshop on Sentiment Analysis Where AI Meets Psychology (SAAIP). Red Hook, NY: Curran.Google Scholar
Bickel, Alexander M. 1962. The Least Dangerous Branch: The Supreme Court at the Bar of Politics. New Haven, CT: Yale University Press.Google Scholar
Bollen, Johan, Mao, Huina, and Pepe, Alberto. 2011. “Modeling Public Mood and Emotion: Twitter Sentiment and Socio-Economic Phenomena.” In Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media, 450–53. Menlo Park, CA: Association for the Advancement of Artificial Intelligence.Google Scholar
Bond, Robert M., Fariss, Christopher J., Jones, Jason J., Kramer, Adam D. I., Marlow, Cameron, Settle, Jaime E., and Fowler, James H. 2012. “A 61-Million-Person Experiment in Social Influence and Political Mobilization.” Nature 489:295–98.CrossRefGoogle ScholarPubMed
Brader, Ted. 2005. “Striking a Responsive Chord: How Political Ads Motivate and Persuade Voters by Appealing to Emotions.” American Journal of Political Science 49 (2): 388–405.CrossRefGoogle Scholar
Bruns, Axel, and Highfield, Tim. 2013. “Political Networks on Twitter: Tweeting the Queensland State Election.” Information, Communication, and Society 16 (5): 667–91.CrossRefGoogle Scholar
Caldeira, Gregory A., and Gibson, James L. 1992. “The Etiology of Public Support for the Supreme Court.” American Journal of Political Science 36 (3): 635–64.CrossRefGoogle Scholar
Carrubba, Clifford J., and Zorn, Christopher. 2010. “Executive Discretion, Judicial Decision Making, and Separation of Powers in the United States.” Journal of Politics 72 (3): 812–24.CrossRefGoogle Scholar
Cataldi, Mario, Di Caro, Luigi, and Schifanella, Claudio. 2010. “Emerging Topic Detection on Twitter Based on Temporal and Social Terms Evaluation.” In Proceedings of the Tenth International Workshop on Multimedia Data Mining. New York: ACM.Google Scholar
Clark, Tom S. 2011. The Limits of Judicial Independence. New York: Cambridge University Press.Google Scholar
Conover, Michael D., Gonçalves, Bruno, Ratkiewicz, Jacob, Flammini, Alessandro, and Menczer, Filippo. 2011. “Predicting the Political Alignment of Twitter Users.” In Privacy, Security, Risk, and Trust (PASSAT) and 2011 IEEE Third International Conference on Social Computing (SocialCom), 192–99. Piscataway, NJ: Institute of Electrical and Electronics Engineers.Google Scholar
Conover, Michael D., Ratkiewicz, J., Francisco, M., Gonçalves, B., Flammini, A., and Menczer, F. 2011. “Political Polarization on Twitter.” In Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media, 89–96. Menlo Park, CA: Association for the Advancement of Artificial Intelligence.Google Scholar
Conway, Bethany Anne, Kenski, Kate, and Wang, Di. 2013. “Twitter Use by Presidential Primary Candidates during the 2012 Campaign.” American Behavioral Scientist 57 (11): 1596–1610.CrossRefGoogle Scholar
Dahl, Robert. 1957. “Decision-Making in a Democracy: The Supreme Court as National Policy-Maker.” Journal of Public Law 6 (2): 279–95.Google Scholar
Davis, Richard. 1994. Decisions and Images: The Supreme Court and the Press. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Franklin, Charles H., and Kosaki, Liane C. 1989. “Republican Schoolmaster: The U.S. Supreme Court, Public Opinion, and Abortion.” American Political Science Review 83 (3): 751–71.CrossRefGoogle ScholarPubMed
Gibson, James L. 1989. “Understandings of Justice: Institutional Legitimacy, Procedural Justice, and Political Tolerance.” Law and Society Review 23 (3): 469–96.CrossRefGoogle Scholar
Gibson, James L., and Caldeira, Gregory A. 2009. Citizens, Courts, and Confirmations. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Gibson, James L., Caldeira, Gregory A., and Lester Kenyatta Spence. 2003. “Measuring Attitudes toward the United States Supreme Court.” British Journal of Political Science 33 (4): 535–56.CrossRefGoogle Scholar
Hibbing, John R., and Theiss-Morse, Elizabeth. 1995. Congress as Public Enemy: Public Attitudes toward American Political Institutions. New York: Cambridge University Press.CrossRefGoogle Scholar
Hibbing, John R., and Theiss-Morse, Elizabeth. 1998. “The Media’s Role in Public Negativity toward Congress: Distinguishing Emotional Reactions and Cognitive Evaluations.” American Journal of Political Science 42 (2): 475–98.CrossRefGoogle Scholar
Hoekstra, Valerie J. 2000. “The Supreme Court and Local Public Opinion.” American Political Science Review 94 (1): 89–100.CrossRefGoogle Scholar
Huckfeldt, R. Robert, and Sprague, John. 1995. Citizens, Politics, and Social Communication: Information and Influence in an Election Campaign. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Huddy, Leonie, Mason, Lilliana, and Aarøe, Lene. 2015. “Expressive Partisanship: Campaign Involvement, Political Emotion, and Partisan Identity.” American Political Science Review 109 (1): 1–17.CrossRefGoogle Scholar
Iyengar, Shanto, and Kinder, Donald R. 1987. News That Matters: Television and American Opinion. Chicago: University of Chicago Press.Google Scholar
Jackman, Simon. 2001. “Multidimensional Analysis of Roll Call Data via Bayesian Simulation: Identification, Estimation, Inference, and Model Checking.” Political Analysis 9 (3): 227–41.CrossRefGoogle Scholar
Johnson, Timothy R., and Martin, Andrew D. 1998. “The Public’s Conditional Response to Supreme Court Decisions.” American Political Science Review 92 (2): 299–309.CrossRefGoogle Scholar
King, Gary, Pan, Jennifer, and Roberts, Margaret E. 2013. “How Censorship in China Allows Government Criticism but Silences Collective Expression.” American Political Science Review 107 (2): 326–43.CrossRefGoogle Scholar
Kwak, Haewoon, Lee, Changhyun, Park, Hosung, and Moon, Sue. 2010. “What Is Twitter, a Social Network or a News Media?” In Proceedings of the 19th International Conference on the World Wide Web, 591–600. New York: ACM.Google Scholar
Larkey, Leah S., Feng, Fangfang, Connell, Margaret, and Lavrenko, Victor. 2004. “Language-Specific Models in Multilingual Topic Tracking.” In Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 402–9. New York: ACM.Google Scholar
Lee, Kyumin, Tamilarasan, Prithivi, and Caverlee, James. 2013. “Crowdturfers, Campaigns, and Social Media: Tracking and Revealing Crowdsourced Manipulation of Social Media.” In International Conference on Web Logs and Social Media. Palo Alto, CA: Association for the Advancement of Artificial Intelligence.Google Scholar
Lodge, Milton, and Tursky, Bernard. 1979. “Comparisons between Category and Magnitude Scaling of Political Opinion Employing SRC/CPS Items.” American Political Science Review 73 (1): 50–66.CrossRefGoogle Scholar
Lupia, Arthur, and Menning, Jesse O. 2009. “When Can Politicians Scare Citizens into Supporting Bad Policies?” American Journal of Political Science 53 (1): 90–106.CrossRefGoogle Scholar
Martin, Andrew D. 2006. “Statutory Battles and Constitutional Wars: Congress and the Supreme Court.” In Institutional Games and the U.S. Supreme Court, ed. Rogers, James R., Flemming, Roy P., and Bond, Jon R. Charlottesville: University of Virginia Press.Google Scholar
Marwick, Alice E., and Boyd, Danah. 2011. “I Tweet Honestly, I Tweet Passionately: Twitter Users, Context Collapse, and the Imagined Audience.” New Media and Society 13 (1): 114–33.CrossRefGoogle Scholar
Mishler, William, and Sheehan, Reginald S. 1996. “Public Opinion, the Attitudinal Model, and Supreme Court Decision Making: A Micro-analytic Perspective.” Journal of Politics 58 (1): 169–200.CrossRefGoogle Scholar
Mislove, Alan, Lehmann, Sune, Ahn, Yong-Yeol, Onnela, Jukka-Pekka, and Niels Rosenquist, J.. 2011. “Understanding the Demographics of Twitter Users.” In Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media. Menlo Park, CA: Association for the Advancement of Artificial Intelligence.Google Scholar
Mondak, Jeffery J. 1994. “Policy Legitimacy and the Supreme Court: The Sources and Contexts of Legitimation.” Political Research Quarterly 47 (3): 675–92.CrossRefGoogle Scholar
Mutz, Diana C. 1997. “Mechanisms of Momentum: Does Thinking Make It So?” Journal of Politics 59 (1): 104–25.CrossRefGoogle Scholar
Mutz, Diana C., and Martin, Paul S. 2001. “Facilitating Communication across Lines of Political Difference: The Role of Mass Media.” American Political Science Review 95 (1): 97–114.CrossRefGoogle Scholar
Nastase, Vivi, and Strapparava, Carlo. 2013. “Bridging Languages through Etymology: The Case of Cross Language Text Categorization.” In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, vol. 1, Long Papers, 651–59. Sofia: Association for Computational Linguistics.Google Scholar
O’Connor, Brendan, Balasubramanyan, Ramnath, Routledge, Bryan R., and Smith, Noah A. 2010. “From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series.” In Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media. Menlo Park, CA: Association for the Advancement of Artificial Intelligence.Google Scholar
Park, Chang Sup. 2013. “Does Twitter Motivate Involvement in Politics? Tweeting, Opinion Leadership, and Political Engagement.” Computers in Human Behavior 29 (4): 1641–48.CrossRefGoogle Scholar
Plummer, Martyn. 2003. “JAGS: A Program for Analysis of Bayesian Graphical Models Using Gibbs Sampling.” Paper presented at the third international workshop on Distributed Statistical Computing (DSC 2003), Vienna University of Technology, March 20–22.Google Scholar
Prior, Markus. 2007. Post-broadcast Democracy: How Media Choice Increases Inequality in Political Involvement and Polarizes Elections. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Qazvinian, Vahed, Rosengren, Emily, Radev, Dragomir R., and Mei, Qiaozhu. 2011. “Rumor Has It: Identifying Misinformation in Microblogs.” In Proceedings of the 19th International Conference on the World Wide Web. New York: ACM.Google Scholar
R Development Core Team. 2009. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing.Google Scholar
Rainie, Lee, Smith, Aaron, Lehman Schlozman, Kay, Brady, Henry, and Verba, Sidney. 2012. “Social Media and Political Engagement.” Pew Research Center, Internet and Technology section. http://www.pewinternet.org/2012/10/19/social-media-and-political-engagement/.Google Scholar
Restuccia, Eric, and Lindstorm, Aaron. 2013. “Federalism and the Authority of the States to Define Marriage.” SCOTUSblog, June 27. http://www.scotusblog.com/2013/06/federalism-and-the-authority-of-the-states-to-define-marriage/.Google Scholar
Rothman, Noah. 2013. “Gay Marriage Rulings Make MSNBC’s Harris-Perry Sad Because They Gut ‘Power of Federal Government.’” Mediaite, June 26. https://www.mediaite.com/tv/consistency-msnbcs-melissa-harris-perry-laments-gutting-power-of-federal-government-in-prop-8-ruling/.Google Scholar
Scheb, John M., and Lyons, William. 2000. “The Myth of Legality and Public Evaluation of the Supreme Court.” Social Science Quarterly 81:928–40.Google Scholar
Sears, David O., and Valentino, Nicholas A. 1997. “Politics Matters: Political Events as Catalysts for Preadult Socialization.” American Political Science Review 91 (1): 45–65.CrossRefGoogle Scholar
Segal, Jeffrey A., and Spaeth, Harold J. 2002. The Supreme Court and the Attitudinal Model Revisited. New York: Cambridge University Press.CrossRefGoogle Scholar
Small, Tamara A. 2011. “What the Hashtag: A Content Analysis of Canadian Politics on Twitter.” Information, Communication, and Society 14 (6): 872–95.CrossRefGoogle Scholar
Staton, Jeffrey K. 2010. Judicial Power and Strategic Communication in Mexico. New York: Cambridge University Press.CrossRefGoogle Scholar
Sunstein, Cass R. 2008. “The Law of Group Polarization.” In Debating Deliberative Democracy, ed. Fishkin, James S. and Laslett, Peter, 80–101. Malden, MA: Blackwell.Google Scholar
Traugott, Michael W., and Price, Vincent. 1992. “A Review: Exit Polls in the 1989 Virginia Gubernatorial Race; Where Did They Go Wrong?” Public Opinion Quarterly 56 (2): 245–53.CrossRefGoogle Scholar
Tumasjan, Andranik, Sprenger, Timm O., Sandner, Philipp G., and Welpe, Isabell M. 2010. “Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment.” In Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media, 178–85. Menlo Park, CA: Association for the Advancement of Artificial Intelligence.Google Scholar
Ura, Joseph Daniel. 2014. “Backlash and Legitimation: Macro Political Responses to Supreme Court Decisions.” American Journal of Political Science 58 (1): 110–26.CrossRefGoogle Scholar
Weeks, Brian E. 2015. “Emotions, Partisanship, and Misperceptions: How Anger and Anxiety Moderate the Effect of Partisan Bias on Susceptibility to Political Misinformation.” Journal of Communication 65 (4): 699–719.CrossRefGoogle Scholar
Wlezien, Christopher. 1995. “The Public as Thermostat: Dynamics of Preference for Spending.” American Journal of Political Science 39:981–1000.CrossRefGoogle Scholar
Yardi, Sarita, and Boyd, Danah. 2010. “Dynamic Debates: An Analysis of Group Polarization over Time on Twitter.” Bulletin of Science, Technology, and Society 30 (5): 316–27.CrossRefGoogle Scholar
Zaller, John R. 1992. The Nature and Origins of Mass Opinion. New York: Cambridge University Press.CrossRefGoogle Scholar
Zhang, Harry. 2004. “The Optimality of Naive Bayes.” In Proceedings of the 17th InternationalFLAIRS Conference. Menlo Park, CA: Association for the Advancement of Artificial Intelligence.Google Scholar