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Quantifying Social Media’s Political Space: Estimating Ideology from Publicly Revealed Preferences on Facebook

  • ROBERT BOND (a1) and SOLOMON MESSING (a2)
Abstract

We demonstrate that social media data represent a useful resource for testing models of legislative and individual-level political behavior and attitudes. First, we develop a model to estimate the ideology of politicians and their supporters using social media data on individual citizens’ endorsements of political figures. Our measure allows us to place politicians and more than 6 million citizens who are active in social media on the same metric. We validate the ideological estimates that result from the scaling process by showing they correlate highly with existing measures of ideology from Congress, and with individual-level self-reported political views. Finally, we use these measures to study the relationship between ideology and age, social relationships and ideology, and the relationship between friend ideology and turnout.

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Copyright
Corresponding author
Robert Bond is Assistant Professor, School of Communication, Ohio State University, 3072 Derby Hall 154 North Oval Mall, Columbus, OH 43210 (bond.136@osu.edu).
Solomon Messing is Research Scientist, Facebook Data Science, 1601 Willow Rd, Menlo Park, CA 94025, (solomon@fb.com).
References
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Abramowitz, Alan. 2010. The Disappearing Center: Engaged Citizens, Polarization and American Democracy. New Haven: Yale University Press.
Abramowitz, Alan, and Jacobson, Gary C.. 2006. Red and Blue Nation? Characteristics and Causes of America’s Polarized Politics. Washington, DC: Brookings Institution Press, chapter “Disconnected or Joined at the Hip?”
Abramowitz, Alan, and Saunders, Kyle. 2008. “Is Polarization a Myth?Journal of Politics 70 (2): 542–55.
Achen, Christopher. 1975. “Mass Political Attitudes and the Survey Response.” American Political Science Review 69 (4): 1218–31.
Aleman, Eduardo, Calvo, Ernesto, Jones, Mark P., and Kaplan, Noah. 2009. “Comparing Cosponsorship and Roll-Call Ideal Points.” Legislative Studies Quarterly 34 (1): 87116.
Ansolabehere, Stephen, Rodden, Jonathan, and Snyder, James M.. 2008. “The Strength of Issues: Using Multiple Measures to Gauge Preference Stability, Ideological Constraint, and Issue Voting.” American Political Science Review 102 (2): 215–32.
Bafumi, Joseph, and Herron, Michael. 2010. “Leapfrog Representation and Extremism: A Study of American Voters and their Members in Congress.” The American Political Science Review 104: 519–42.
Bailey, Michael. 2007. “Comparable Preference Estimates Across Time and Institutions for the Court, Congress, and Presidency.” American Journal of Political Science 51: 433–48.
Baldassarri, Delia, and Goldberg, Amir. 2014. “Neither Ideologues, nor Agnostics: Alternative Voters’ Belief System in an Age of Partisan Politics.” American Journal of Sociology (forthcoming).
Barberá, Pablo. 2014. “Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data..” Political Analysis (forthcoming).
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 (7415): 295–8.
Bonica, Adam. 2013. “Ideology and Interests in the Political Marketplace.” American Journal of Political Science 57 (2): 294311.
Butler, Daniel M., and Broockman, David E.. 2011. “Do Politicians Racially Discriminate Against Constituents? A Field Experiment on State Legislators.” American Journal of Political Science 55 (3): 463–77.
Butler, Daniel M., Karpowitz, Christopher F., and Pope, Jeremy C.. 2012. “A Field Experiment on Legislators’ Home Styles: Service versus Policy.” The Journal of Politics 74 (02), 474–86.
Campbell, Angus, Converse, Philip E., Miller, Warren E., and Stokes, Donald E.. 1960. The American Voter. Chicago and London: University of Chicago Press.
Clinton, Joshua, Jackman, Simon, and Rivers, Douglas. 2004. “The Statistical Analysis of Roll Call Data.” The American Political Science Review 98 (2): 355–70.
Converse, Philip. 2006. “The Nature of Belief Systems in Mass Publics.” Critical Review 18 (1–3): 174.
Cornelis, Ilse, Hiel, Alain Van, Roets, Arne, and Kossowska, Malgorzata. 2009. “Age Differences in Conservatism: Evidence on the Mediating Effects of Personality and Cognitive Style.” Journal of Personality 77 (1): 5188.
de Sola Pool, Ithel, Abelson, Robert P., and Popkin, Samuel. 1956. Candidates, Issues and Strategies. Cambridge, MA: MIT Press.
Dimaggio, Paul, Evans, John, and Bryson, Bethany. 1996. “Have Americans’ Social Attitudes Become More Polarized?American Journal of Sociology 102: 690755.
Eckart, Carl, and Young, Gale. 1936. “The Approximation of One Matrix by Another of Lower Rank.” Psychometrika 1 (3): 211–8.
Eveland, William P. Jr., and Hively, Myiah Hutchens. 2009. “Political Discussion Frequency, Network Size, and “Heterogeneity” of Discussion as Predictors of Political Knowledge and Participation.” Journal of Communication 59 (2): 204–24.
Facebook. 2011. “Statistics.” http://www.facebook.com/press/info.php?statistics
Feldman, Stanley. 1998. “Structure and Consistency in Public Opinion: The Role of Core Beliefs and Values.” American Journal of Political Science 32 (2): 416–40.
Festinger, Leon. 1957. A Theory of Cognitive Dissonance. Evanston, IL: Row Peterson.
Fiorina, Morris, Abrams, Samuel, and Pope, Jeremy. 2006. Culture War? The Myth of a Polarized America. New York: Pearson Longman.
Fiorina, Morris, and Levendusky, Matthew. 2006. Red and Blue Nation? Characteristics and Causes of America’s Polarized Politics. Washington, DC: Brookings Institution Press, chapter “Disconnected: The Political Class versus the People.”
Gerber, Elisabeth R., and Lewis, Jeffrey B.. 2004. “Beyond the Median: Voter Preferences, District Heterogeneity, and Political Representation.” Journal of Political Economy 112 (6): 1364–83.
Glenn, Norval D. 1974. “Aging and Conservatism.” The ANNALS of the American Academy of Political and Social Science 415 (1): 176–86.
Goldberg, Amir. 2011. “Mapping Shared Understandings Using Relational Class Analysis: The Case of the Cultural Omnivore Reexamined.” American Journal of Sociology 116 (5): 1397–436.
Grimmer, Justin, Messing, Solomon, and Westwood, Sean J.. 2012. “How Words and Money Cultivate a Personal Vote: The Effect of Legislator Credit Claiming on Constituent Credit Allocation.” American Political Science Review 106 (04): 703–19.
Hatemi, Peter, Gillespie, Nathan, Eaves, Lindon, Maher, Brion, Webb, Bradley, Heath, Andrew, Medland, Sarah, Smyth, David, Beeby, Harry, Gordon, Scott, Mongomery, Grant, Zhu, Ghu, Byrne, Enda, and Martin, Nicholas. 2011. “A Genome-Wide Analysis of Liberal and Conservative Political Attitudes.” Journal of Politics 73 (1): 115.
Heider, F. 1944. “Social Perception and Phenomenal Causality.” Psychological Review 51 (6): 358–74.
Hix, Simon. 1999. “Dimensions and Alignments in European Union Politics: Cognitive Constraints and Partisan Responses.” European Journal of Political Research 35 (1): 69106.
Hix, Simon, Noury, Abdul, and Roland, Gerard. 2006. “Dimensions of Politics in the European Parliament.” American Journal of Political Science 50 (2): 494520.
Huckfeldt, Robert, Johnson, Paul E., and Sprague, John. 2004. Political Disagreement: The Survival of Diverse Opinions within Communication Networks. New York: Cambridge University Press.
Huckfeldt, Robert, Mendez, Jeanette M., and Osborn, Tracy L.. 2004. “Disagreement, Ambivalence, and Engagement: The Political Consequences of Heterogeneous Networks.” Political Psychology 25 (1): 6595.
Jackson, John E. 1983. “The Systematic Beliefs of the Mass Public: Estimating Policy Preferences with Survey Data.” Journal of Politics 45 (4): 840–65.
Jennings, M. Kent, and Niemi, Richard G.. 1978. “The Persistence of Political Orientations: An Over-Time Analysis of Two Generations.” British Journal of Political Science 8 (3): 333–63.
Jones, Jason J., Bond, Robert M., Fariss, Christopher J., Settle, Jaime E., Kramer, Adam D. I., Marlow, Cameron, and Fowler, James H.. 2012. “Yahtzee: An Anonymized Group Level Matching Procedure.” PLoS ONE 8 (2): 55760.
Jones, Jason J., Settle, Jaime E., Bond, Robert M., Fariss, Christopher J., Marlow, Cameron, and Fowler, James H.. 2012. “Inferring Tie Strength from Online Directed Behavior.” PLoS ONE 8 (1): e52168.
Kinder, Donald. 1983. Diversity and Complexity in American Public Opinion. Washington, DC: APSA Press, 389425.
King, Gary, Tomz, Michael, and Wittenberg, Jason. 2000. “Making the Most of Statistical Analyses: Improving Interpretation and Presentation.” American Journal of Political Science 44 (2): 347361.
Klofstad, Casey, McDermott, Rose, and Hatemi, Peter. 2013. “The Dating Preferences of Liberals and Conservatives.” Political Behavior 35: 519–38.
Kohut, Andrew, Parker, Kim, Keeter, Scott, Doherty, Carroll, and Dimock, Michael. 2007. “How Young People View Their Lives, Futures and Politics: A Portrait of ‘Generation Next’.” http://www.people-press.org/files/legacy-pdf/300.pdf
Krosnick, Jon A., and Alwin, Duane F.. 1989. “Aging and Susceptibility to Attitude Change.” Journal of Personality and Social Psychology 57: 416–25.
Laver, Michael, Benoit, Kenneth, and Garry, John. 2003. “Extracting Policy Positions from Political Texts Using Words as Data.” The American Political Science Review 97 (2): 311–32.
Lazer, David, Pentland, Alex, Adamic, Lada, Aral, Sinan, Barabasi, Albert Laszlo, Brewer, Devon, Christakis, Nicholas, Contractor, Noshir, Fowler, James, Gutmann, Myron, Jebara, Tony, King, Gary, Macy, Michael, Roy, Deb, and Alstyne, Marshall Van. 2009. “Computational Social Science.” Science 323: 721–23.
Lazer, David, Rubineau, Brian, Chetkovich, Carol, Katz, Nancy, and Neblo, Michael. 2010. “The Coevolution of Networks and Political Attitudes.” Political Communication 27 (3): 248–74. http://www.tandfonline.com/doi/abs/10.1080/10584609.2010.500187
Levendusky, Matthew. 2009. The Partisan Sort: How Liberals Became Democrats and Conservatives Became Republicans. Chicago: The University of Chicago Press.
Malbin, Michael J. 2009. “Small Donors, Large Donors and the Internet: The Case for Public Financing after Obama.” Unpublished manuscript.
Martin, Andrew D., and Quinn, Kevin M.. 2002. “Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953–1999.” Political Analysis 10 (2): 134–53.
McCarty, Nolan, Poole, Keith T., and Rosenthal, Howard. 2006. Polarized America: The Dance of Ideology and Unequal Riches. Cambridge, MA: MIT Press.
McClurg, Scott. 2006. “The Electoral Relevance of Political Talk: Examining Disagreement and Expertise Effects in Social Networks on Political Participation.” American Journal of Political Science 50 (3): 737–54.
Messing, Solomon, and Westwood, Sean. 2012. “Selective Exposure in the Age of Social Media: Endorsements Trump Partisan Source Affiliation when Selecting Online News Media.” Communication Research, 41 (8): 1042–63.
Monroe, Burt L., Colaresi, Michael, and Quinn, Kevin. 2009. “Fightin’ Words: Lexical Feature Selection and Evaluation for Identifying the Content of Political Conflict.” Political Analysis 15 (4): 372403.
Monroe, Burt L., and Maeda, Ko. 2004. Rhetorical Ideal Point Estimation: Mapping Legislative Speech. Palo Alto: Stanford University.
Mutz, Diana. 2002. “The Consequences of Cross-Cutting Networks for Political Participation.” American Journal of Political Science 46 (4): 838–55.
Mutz, Diana C., and Young, Lori. 2011. “Communication and Public Opinion Plus Ca Change?Public Opinion Quarterly 75 (5): 1018–44.
Newcomb, Theodore Mead. 1943. Personality & Social Change; Attitude Formation in a Student Community. New York: Dryden Press.
Pew. 2012. “Internet Gains Most as Campaign News Source but Cable TV Still Leads: Social Media Doubles, but Remains Limited.” http://www.journalism.org/commentary_backgrounder/social_media_doubles_remains_limited
Poole, Keith. 2005. Spatial Models of Parliamentary Voting. New York: Cambridge University Press.
Poole, Keith, and Rosenthal, Howard. 1997. Ideology and Congress. New Brunswick, NJ: Transaction Publishers.
Ray, John J. 1985. “What Old People Believe: Age, Sex, and Conservatism.” Political Psychology 6 (3): 525–28.
Scheufele, Dietram A., Nisbet, Matthew C., Brossard, Dominique, and Nisbet, Erik C.. 2004. “Social Structure and Citizenship: Examining the Impacts of Social Setting, Network Heterogeneity, and Informational Variables on Political Participation.” Political Communication 21 (3): 315–38.
Schiffer, Adam J. 2000. “I’m Not That Liberal: Explaining Conservative Democratic Identification.” Political Behavior 22 (4): 293310.
Talbert, Jeffery C., and Potoski, Matthew. 2009. “Setting the Legislative Agenda: The Dimensional Structure of Bill Cosponsoring and Floor Voting.” Journal of Politics 64 (3): 864–91.
Tausanovitch, Chris, and Warshaw, Christopher. 2012. “Representation in Congress, State Legislatures and Cities.” Unpublished manuscript.
Treier, Shawn, and Hillygus, D. Sunshine. 2009. “The Nature of Political Ideology in the Contemporary Electorate.” Public Opinion Quarterly 73 (4): 679703.
Williams, Rick L. 2000. “A Note on Robust Variance Estimation for Cluster-Correlated Data.” Biometrics 56 (2): 645–6.
Wojcieszak, Magdalena E., and Mutz, Diana C.. 2009. “Online Groups and Political Discourse: Do Online Discussion Spaces Facilitate Exposure to Political Disagreement?Journal of Communication 59 (1): 4056.
Wood, Thomas, and Oliver, Eric. 2012. “Toward a More Reliable Implementation of Ideology in Measures of Public Opinion.” Public Opinion Quarterly 76 (4): 636–62.
Wooldridge, Jeffrey M. 2002. Econometric Analysis of Cross Section and Panel Data. Boston: The MIT Press.
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