research-article

Revisiting The American Voter on Twitter

Authors:

Padmini SrinivasanAuthors Info & Claims

CHI '17: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

Pages 4507 - 4519

https://doi.org/10.1145/3025453.3025543

Published: 02 May 2017 Publication History

Abstract

The American Voter - a seminal work in political science - uncovered the multifaceted nature of voting behavior which has been corroborated in electoral research for decades since. In this paper, we leverage The American Voter as an analysis framework in the realm of computational political science, employing the factors of party, personality, and policy to structure the analysis of public discourse on online social media during the 2016 U.S. presidential primaries. Our analysis of 50 million tweets reveals the continuing importance of these three factors; our understanding is also enriched by the application of sentiment analysis techniques. The overwhelmingly negative sentiment of conversations surrounding 10 major presidential candidates reveals more "crosstalk" from Democratic leaning users towards Republican candidates, and less vice-versa. We uncover the lack of moderation as the most discussed personality dimension during this campaign season, as the political field becomes more extreme - Clinton and Rubio are perceived as moderate, while Trump, Sanders, and Cruz are not. While the most discussed issues are foreign policy and immigration, Republicans tweet more about abortion than Democrats who tweet more about gay rights than Republicans. Finally, we illustrate the importance of multifaceted political discourse analysis by applying regression to quantify the impact of party, personality, and policy on national polls.

References

[1]

2013. New Tweets per second record, and how! https://blog.twitter.com/2013/new-tweets-per-second-record-and-how. (August 2013).

[2]

2016. Donald Trump: Ban all Muslim travel to U.S. http://www.cnn.com/2015/12/07/politics/donald-trump-muslim-ban-immigration/. (December 2016).

[3]

2016. Election 2016 Presidential Polls. http://www.realclearpolitics.com/epolls/latest_polls/president/. (2016).

[4]

2016. Fiorina: Obama 'delusional' about magnitude of climate change as security threat. http://www.foxnews.com/politics/2015/11/29/fiorina-obama-delusional-about-magnitude-climate-change-as-security-threat.html. (November 2016).

[5]

Alan Abramowitz and Steven Webster. 2015. All politics is national: The rise of negative partisanship and the nationalization of US house and senate elections in the 21st century. In Annual Meeting of the Midwest Political Science Association Conference.

[6]

Hunt Allcott and Matthew Gentzkow. 2017. Social Media and Fake News in the 2016 Election. (January 2017). NBER Working Paper No. 23089.

[7]

Stefano Baccianella, Andrea Esuli, and Fabrizio Sebastiani. 2010. SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining. In LREC, Vol. 10. 2200--2204.

[8]

Eytan Bakshy, Solomon Messing, and Lada Adamic. 2015. Exposure to Ideologically Diverse News and Opinion on Facebook. Science 348, 6239 (May 2015), 1130--1132.

[9]

Pablo Barberá, John T. Jost, Jonathan Nagler, Joshua A. Tucker, and Richard Bonneau. 2015. Tweeting From Left to Right: Is Online Political Communication More Than an Echo Chamber? Psychological Science (August 2015).

[10]

Larry M. Bartels. 2002. Beyond the Running Tally: Partisan Bias in Political Perceptions. Political Behavior 24, 2 (Jun 2002), 117--150.

[11]

Frank R. Baumgartner, F. R. tner and Bryan D. Jones. 1993. Agendas and Instability in American Politics. Chicago : University of Chicago Press.

[12]

William M. Benoit. 2004. Political Party Affiliation and Presidential Campaign Discourse. Communication Quarterly 52, 2 (2004), 81--97.

[13]

Adam Bermingham and Alan F. Smeaton. 2011. On Using Twitter to Monitor Political Sentiment and Predict Election Results. In Sentiment Analysis where AI meets Psychology.

[14]

Sanmitra Bhattacharya, Chao Yang, Padmini Srinivasan, and Bob Boynton. 2015. Perceptions of Presidential Candidates' Personality in Twitter. Journal of the Association for Information Science and Technology (2015).

Digital Library

[15]

Pete Burnap, Rachel Gibson, Luke Sloan, Rosalynd Southern, and Matthew Williams. 2015. 140 Characters to Victory?: Using Twitter to Predict the UK 2015 General Election. Cardiff University (working paper) (2015).

[16]

Angus Campbell, Converse Philip, Miller Warren, and Stokes Donald. 1960. The American Voter. University of Chicago Press.

[17]

Pew Research Center. 2015. A Deep Dive Into Party Affiliation. http://www.people-press.org/2015/04/07/a-deep-dive-into-party-affiliation/. (April 2015).

[18]

Andrea Ceron, Luigi Curini, and Stefano M. Iacus. 2014. Every tweet counts? How sentiment analysis of social media can improve our knowledge of citizens' political preferences with an application to Italy and France. New Media & Society 16, 2 (2014), 340--358.

[19]

Roger W. Cobb and Charles D. Elder. 1972. Participation in American Politics: The Dynamics of Agenda Building. Johns Hopkins University Press.

[20]

Raviv Cohen and Derek Ruths. 2013. Classifying Political Orientation on Twitter: It's Not Easy!. In Proceedings of the Seventh International AAAI Conference on Weblogs and Social Media (ICWSM).

[21]

Michael D. Conover, Bruno Gonçalves, Jacob Ratkiewicz, Alessandro Flammini, and Filippo Menczer. 2011a. Predicting the political alignment of Twitter users. Proceedings of the International Conference on Social Computing (2011).

[22]

Michael D. Conover, Jacob Ratkiewicz, Matthew Francisco, Bruno Gonçalves, Filippo Menczer, and Alessandro Flammini. 2011b. Political Polarization on Twitter. In AAAI International Conference on Weblogs and Social Media (ICWSM).

[23]

Edmond Costantini and Kenneth H. Craik. 1980. Personality and politicians: California party leaders, 1960-1976. Personality and Social Psychology 38, 4 (1980), 641--661.

[24]

Joseph DiGrazia, Karissa McKelvey, Johan Bollen, and Fabio Rojas. 2013. More tweets, more votes: Social media as a quantitative indicator of political behavior. PLOS ONE 11, 8 (2013).

[25]

Patrick Dolan. 2011. Abortion and American Politics: Can a single policy issue lead to party switching? Breithaupt American Government Paper Competition, Roanoke College. (April 2011).

[26]

Adam Edelman. 2016. 2016 candidate John Kasich: I would create a NEW government agency that would 'promote Judeo-Christian values'. http://www.nydailynews.com/news/politics/kasich-create-agency-push-judeo-christian-values-article-1.2439022. (November 2016).

[27]

Pew Research Center for the People & the Press. 2012a. Obama in a Word: From 'Inexperienced' and 'Change' to 'Good' and 'Trying'. http://www.people-press.org/2012/09/05/obama-in-a-word-from-inexperienced-and-change-to-good-and-trying/. (September 2012).

[28]

Pew Research Center for the People & the Press. 2012b. Romney in a Word: 'Honest,' 'Businessman,' 'Rich'. http://www.people-press.org/2012/08/29/romney-in-a-word-honest-businessman-rich/. (August 2012).

[29]

Maryann E. Gallagher and Susan H. Allen. 2014. Presidential Personality: Not Just a Nuisance. Foreign Policy Analysis 10, 1 (January 2014), 1--21.

[30]

Daniel Gayo-Avello. 2012. "I Wanted to Predict Elections with Twitter and all I got was this Lousy Paper" - A Balanced Survey on Election Prediction using Twitter Data. arXiv: 12046441 (2012).

[31]

Daniel Gayo-Avello, Panagiotis T. Metaxas, and Eni Mustafaraj. 2011. Limits of Electoral Predictions Using Twitter. In AAAI International Conference on Weblogs and Social Media (ICWSM).

[32]

Alexander L. George and Juliette L. George. 1998. Presidential personality and performance. Boulder, CO: Westview Press.

[33]

Jennifer Golbeck and Derek Hansen. 2014. A method for computing political preference among Twitter followers. Social Networks (2014).

[34]

Jeffrey Gottfried, Michael Barthel, Elisa Shearer, and Amy Mitchell. 2016. The 2016 Presidential Campaign - a News Event That's Hard to Miss. http://www.journalism.org/2016/02/04/the-2016-presidential-campaign-a-news-event-thats-hard-to-miss/. (February 2016).

[35]

Harrison G. Gough and Alfred B. Heilbrun. 1983. The Adjective Check List Manual. Consulting Psychologists Press. (1983).

[36]

Benjamin Highton. 2012. Updating Political Evaluations: Policy Attitudes, Partisanship, and Presidential Assessments. Political Behavior 34, 1 (March 2012), 57--78.

[37]

Ryan Holmes. 2016. How Bernie Sanders Beats Donald Trump at Social Media. http://fortune.com/2016/04/18/bernie-sanders-donald-trump-social-media/. (April 2016).

[38]

Sounman Hong and Daniel Nadler. 2012. Which candidates do the public discuss online in an election campaign? The use of social media by 2012 presidential candidates and its impact on candidate salience. Government Information Quarterly 29, 4 (2012), 455--461.

[39]

Andreas Jungherr, Pascal Jürgens, and Harald Schoen. 2012. Why the Pirate Party Won the German Election of 2009 or The Trouble With Predictions. Social Science Computer Review 2, 30 (2012), 229--234.

Digital Library

[40]

Michael Lewis-Beck, Jacoby G. William, Norpath Helmut, and Weisberg F. Herbert. 2008. The American Voter Revisited. University of Michigan Press.

[41]

Yelena Mejova, Padmini Srinivasan, and Bob Boynton. 2013. GOP Primary Season on Twitter: "Popular" Political Sentiment in Social Media. In WSDM.

Digital Library

[42]

Jonathan Scott Morgan, Cliff Lampe, and M.Z. Shafiq. 2013. Is news sharing on Twitter ideologically biased? In ACM Conference on Computer Supported Cooperative Work (CSCW).

Digital Library

[43]

Brendan O'Connor, Ramnath Balasubramanyan, Bryan R. Routledge, and Noah A. Smith. 2010. From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series. In AAAI International Conference on Weblogs and Social Media (ICWSM).

[44]

Alexandra Olteanu, Carlos Castillo, Fernando Diaz, and Sarah Vieweg. 2014. CrisisLex: A Lexicon for Collecting and Filtering Microblogged Communications in Crises. In AAAI International Conference on Weblogs and Social Media (ICWSM).

[45]

Marco Pennacchiotti and Ana-Maria Popescu. 2011. A Machine Learning Approach to Twitter User Classification. AAAI International Conference on Weblogs and Social Media (ICWSM) (2011).

[46]

Terri Rupar, Aaron Blake, and Samuel Granados. 2015. The ever-changing issues of the 2016 campaign, as seen on Twitter. http://wapo.st/1OgbJ45. (December 2015).

[47]

Erik T. K. Sang and Johan Bos. 2012. Predicting the 2011 Dutch senate election results with Twitter. In Workshop on Semantic Analysis in Social Media (SASN).

Digital Library

[48]

David O. Sears and Jonathan L. Freedman. 1967. Selective Exposure to Information: A Critical Review. Public Opinion Quarterly 31, 2 (1967), 194--213.

[49]

Dean K. Simonton. 1986. Presidential Personality: Biographical Use of the Gough Adjective Check List. Journal of Personality and Social Psychology 51, 1 (1986), 149--160.

[50]

Marko Skoric and Nathaniel Poor. 2012. Tweets and votes: A study of the 2011 Singapore general election. In Hawaii International Conference on System Sciences (HICSS).

Digital Library

[51]

Aaron Smith. 2014. Cell Phones, Social Media and Campaign 2014. Pew Research Center. (November 2014).

[52]

Stefan Stieglitz and Linh X. Dang. 2013. Social media and political communication: a social media analytics framework. Social Network Analysis and Mining 4, 4 (December 2013), 1277--1291.

[53]

Andranik Tumasjan, Timm O. Sprenger, Philipp G. Sandner, and Isabell M. Welpe. 2010. Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment. In AAAI International Conference on Weblogs and Social Media (ICWSM).

[54]

Hao Wang, Dogan Can, Abe Kazemzadeh, François Bar, and Shrikanth Narayanan. 2012. A System for Real-time Twitter Sentiment Analysis of 2012 U.S. Presidential Election Cycle. In 50th Annual Meeting of the Association for Computational Linguistics. 115--120.

Digital Library

[55]

Dan B. Wood and Alesha Doan. 2003. The Politics of Problem Definition: A Theory and Application to Sexual Harassment. American Journal of Political Science 47, 4 (October 2003), 640--653.

[56]

Dan B. Wood and Arnold Vedlitz. 2007. Issue Definition, Information Processing, and the Politics of Global Warming. American Journal of Political Science 51, 3 (July 2007), 552--568.

[57]

Faiyaz A. Zamal, Wendy Liu, and Derek Ruths. 2012. Homophily and latent attribute inference: Inferring latent attributes of Twitter users from neighbors. AAAI International Conference on Weblogs and Social Media (ICWSM) (2012).

[58]

Amy X. Zhang and Scott Counts. 2015. Modeling Ideology and Predicting Policy Change with Social Media: Case of Same-Sex Marriage. ACM Conference on Human Factors in Computing Systems (CHI) (2015).

Digital Library

[59]

Daniel X. Zhou, Paul Resnick, and Qiaozhu Mei. 2011. Classifying the Political Leaning of News Articles and Users from User Votes. In AAAI International Conference on Weblogs and Social Media (ICWSM).

Cited By

Palacin VMcDonald SAragón PNelimarkka M(2024)Configurations of Digital Participatory BudgetingACM Transactions on Computer-Human Interaction10.1145/363514431:2(1-28)Online publication date: 5-Feb-2024
https://dl.acm.org/doi/10.1145/3635144
Taylor JSimpson ETran ABrubaker JFox SZhu H(2024)Cruising Queer HCI on the DL: A Literature Review of LGBTQ+ People in HCIProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642494(1-21)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642494
Ravi KYuan J(2024)Ideological orientation and extremism detection in online social networking sites: A systematic reviewIntelligent Systems with Applications10.1016/j.iswa.2024.20045624(200456)Online publication date: Dec-2024
https://doi.org/10.1016/j.iswa.2024.200456
Show More Cited By

Index Terms

Revisiting The American Voter on Twitter
1. Social and professional topics
  1. Professional topics
    1. Computing and business

Recommendations

The 2014 Indian elections on Twitter

The study examines Twitter political campaigns in the 2014 Indian general election.It also examines the role of internet and first time voters in electoral success.New-and-upcoming parties used Twitter for self-promotion and media validation.The winning ...
Modelling political disaffection from Twitter data
WISDOM '13: Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining

Twitter is one of the most popular micro-blogging services in the world, often studied in the context of political opinion mining for its peculiar nature of online public discussion platform. In our work we analyse the phenomenon of political ...
On tweets, retweets, hashtags and user profiles in the 2016 American Presidential Election Scene
dg.o '17: Proceedings of the 18th Annual International Conference on Digital Government Research

Twitter is a microblogging where users can publish short messages restricted to 140 characters. It has been used in the political scene from different perspectives. One of them is predicting election results. In this area, many researchers have drawn ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

CHI '17: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

May 2017

7138 pages

ISBN:9781450346559

DOI:10.1145/3025453

General Chairs:
Gloria Mark
University of California Irvine
,
Susan Fussell
Cornell University
,
Program Chairs:
Cliff Lampe
University of Michigan
,
m.c. schraefel
University of Southampton
,
Juan Pablo Hourcade
University of Iowa
,
Caroline Appert
Université Paris-Sud
,
Daniel Wigdor
University of Toronto

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 May 2017

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

CHI '17

Sponsor:

SIGCHI

CHI '17: CHI Conference on Human Factors in Computing Systems

May 6 - 11, 2017

Colorado, Denver, USA

Acceptance Rates

CHI '17 Paper Acceptance Rate 600 of 2,400 submissions, 25%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

Upcoming Conference

CHI '25

Sponsor:
sigchi

CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

Yokohama , Japan

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

18
Total Citations
View Citations
679
Total Downloads

Downloads (Last 12 months)41
Downloads (Last 6 weeks)1

Reflects downloads up to 26 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Palacin VMcDonald SAragón PNelimarkka M(2024)Configurations of Digital Participatory BudgetingACM Transactions on Computer-Human Interaction10.1145/363514431:2(1-28)Online publication date: 5-Feb-2024
https://dl.acm.org/doi/10.1145/3635144
Taylor JSimpson ETran ABrubaker JFox SZhu H(2024)Cruising Queer HCI on the DL: A Literature Review of LGBTQ+ People in HCIProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642494(1-21)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642494
Ravi KYuan J(2024)Ideological orientation and extremism detection in online social networking sites: A systematic reviewIntelligent Systems with Applications10.1016/j.iswa.2024.20045624(200456)Online publication date: Dec-2024
https://doi.org/10.1016/j.iswa.2024.200456
Yu XWojcieszak MCasas A(2023)Partisanship on Social Media: In-Party Love Among American Politicians, Greater Engagement with Out-Party Hate Among Ordinary UsersPolitical Behavior10.1007/s11109-022-09850-x46:2(799-824)Online publication date: 8-Jan-2023
https://doi.org/10.1007/s11109-022-09850-x
Grimaldi DCely JArboleda H(2020)Inferring the votes in a new political landscape: the case of the 2019 Spanish Presidential electionsJournal of Big Data10.1186/s40537-020-00334-57:1Online publication date: 6-Aug-2020
https://doi.org/10.1186/s40537-020-00334-5
Grön KNelimarkka M(2020)Party Politics, Values and the Design of Social Media ServicesProceedings of the ACM on Human-Computer Interaction10.1145/34151754:CSCW2(1-29)Online publication date: 15-Oct-2020
https://dl.acm.org/doi/10.1145/3415175
Haq EBraud TKwon YHui P(2020)A Survey on Computational PoliticsIEEE Access10.1109/ACCESS.2020.30349838(197379-197406)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3034983
Zannettou SCaulfield TDe Cristofaro ESirivianos MStringhini GBlackburn J(2019)Disinformation Warfare: Understanding State-Sponsored Trolls on Twitter and Their Influence on the WebCompanion Proceedings of The 2019 World Wide Web Conference10.1145/3308560.3316495(218-226)Online publication date: 13-May-2019
https://dl.acm.org/doi/10.1145/3308560.3316495
Le HMaragh REkdale BHigh AHavens TShafiq Z(2019)Measuring Political Personalization of Google News SearchThe World Wide Web Conference10.1145/3308558.3313682(2957-2963)Online publication date: 13-May-2019
https://dl.acm.org/doi/10.1145/3308558.3313682
Zannettou SCaulfield TSetzer WSirivianos MStringhini GBlackburn JBoldi PWelles BKinder-Kurlanda KWilson CPeters IMeira W(2019)Who Let The Trolls Out?Proceedings of the 10th ACM Conference on Web Science10.1145/3292522.3326016(353-362)Online publication date: 26-Jun-2019
https://dl.acm.org/doi/10.1145/3292522.3326016
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents