Can we vote with our tweet? On the perennial difficulty of election forecasting with social media

International Journal of Forecasting

Volumn 31, Issue 3, 2015, Pages 992-1007

  Huberty, Mark ^a  

^a NONE   (United States)

Author keywords

Elections.; Evaluating forecasts.; Model selection.; Social media; Surveys.

Indexed keywords

EID: 84925356925     PISSN: 01692070     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijforecast.2014.08.005     Document Type: Article

References (50)

1. Barberá, P. (2012). Birds of the same feather tweet together: Bayesian ideal point estimation using Twitter data. APSA 2012 annual meeting paper.
2. Beauchamp, N. (2013). Predicting and interpolating state-level polling using Twitter textual data. Working paper, Northeastern University.
3. Bermingham A., Smeaton A.F. On using Twitter to monitor political sentiment and predict election results. Sentiment Analysis where AI meets Psychology (SAAIP) 2011, 2.
4. Binns A. Don't feed the trolls! Managing troublemakers in magazines' online communities. Journalism Practice 2012, 6(4):547-562.
5. Blei D., Ng A., Jordan M. Latent Dirichlet Allocation. The Journal of Machine Learning Research 2003, 3:993-1022.
6. Blondel V.D., Guillaume J.-L., Lambiotte R., Lefebvre E. Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment 2008, 2008(10):P10008.
7. Bond R.M., Fariss C.J., Jones J.J., Kramer A.D., Marlow C., Settle J.E., Fowler J.H. A 61-million-person experiment in social influence and political mobilization. Nature 2012, 489(7415):295-298.
8. Boyle J., Fleeman A., Kennedy C., Lewis F., Weiss A. Sampling cell phone only households: A comparison of demographic and behavioral characteristics from ABS and cell phone samples. Survey Practice 2013, 5(1).
9. Broockman D.E., Green D.P. Do online advertisements increase political candidates' name recognition or favorability? Evidence from randomized field experiments. Political Behavior 2013, 1-27.
10. Butler D. When Google got flu wrong. Nature 2013, 494(7436):155.
11. Caughey D., Sekhon J.S. Elections and the regression discontinuity design: Lessons from close US House races, 1942-2008. Political Analysis 2011, 19(4):385-408.
12. Choi H., Varian H. Predicting the present with Google trends. Economic Record 2012, 88(s1):2-9.
13. Christian, L., Keeter, S., Purcell, K., & Smith, A. (2010). Assessing the cell phone challenge to survey research in 2010. Technical report, The Pew Research Center.
14. Conover, M. D., Ratkiewicz, J., Francisco, M., Goncalves, B., Flammini, A., & Menczer, F. (2011). Political polarization on Twitter. In Proceedings of the fifth international AAAI conference on weblogs and social media.
15. Copeland, P., Romano, R., Zhang, T., Hecht, G., Zigmond, D., & Stefansen, C. (2013). Google disease trends: an update. International society of neglected tropical diseases.
16. DiGrazia, J., McKelvey, K., Bollen, J., & Rojas, F. (2013). More tweets, more votes: Social media as a quantitative indicator of political behavior. Working paper, Indiana University.
17. Gayo-Avello, D. (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 preprint . arxiv:1204.6441.
18. Gayo-Avello, D., Metaxas, P. T., & Mustafaraj, E. (2011). Limits of electoral predictions using Twitter. In Proceedings of the international conference on weblogs and social media (ICWSM) 2011, July 17, volume21.
19. Ginsberg J., Mohebbi M., Patel R., Brammer L., Smolinski M., Brilliant L. Detecting influenza epidemics using search engine query data. Nature 2008, 457(7232):1012-1014.
20. Grimmer J., Stewart B.M. Text as data: The promise and pitfalls of automatic content analysis methods for political texts. Political Analysis 2013, 21(3):267-297.
21. Hill, K. (2012). How Target figured out a teen girl was pregnant before her father did. Forbes.com, 16 February.
22. Huberty, M. (2013). Multi-cycle forecasting of congressional elections with social media. In Workshop on politics, elections, and data (PLEAD) 2013.
23. Jungherr A., Jürgens P., Schoen H. Why the Pirate Party won the German election of 2009 or the trouble with predictions: A response to Tumasjan, A., Sprenger, T.O., Sander, P.G., & Welpe, I.M. "Predicting elections with Twitter: What 140 characters reveal about political sentiment". Social Science Computer Review 2012, 30(2):229-234.
24. Keeter S., Kennedy C., Dimock M., Best J., Craighill P. Gauging the impact of growing nonresponse on estimates from a national RDD telephone survey. Public Opinion Quarterly 2006, 70(5):759-779.
25. Kohut, A., Keeter, S., Doherty, C., Dimock, M., & Christian, L. (2012). Assessing the representativeness of public opinion surveys. Pew Research Center for the People and the Press. May 15, 2012. Technical report.
26. Lessig, L. (1999). Code: And other laws of cyberspace. Basic books.
27. Levenshus A. Online relationship management in a presidential campaign: A case study of the Obama campaign's management of its internet-integrated grassroots effort. Journal of Public Relations Research 2010, 22(3):313-335.
28. Manyika J., Chui M., Brown B., Bughin J., Dobbs R., Roxburgh C., Byers A.H. Big data: The next frontier for innovation, competition, and productivity 2011, Mckinsey & Company.
29. Metaxas P.T., Mustafaraj E., Gayo-Avello D. How (not) to predict elections. 2011 IEEE third international conference on social computing 2011, 165-171. IEEE.
30. Morstatter F., Pfeffer J., Liu H., Carley K.M. Is the sample good enough? Comparing data from Twitter's Streaming API with Twitter's Firehose. Proceedings of ICWSM 2013.
31. Muchnik L., Aral S., Taylor S.J. Social influence bias: A randomized experiment. Science 2013, 341(6146):647-651.
32. O'Connor, B., Balasubramanyan, R., Routledge, B., & Smith, N. (2010). From tweets to polls: Linking text sentiment to public opinion time series. In Proceedings of the international AAAI conference on weblogs and social media, (pp. 122-129).
33. Owoputi, O., O'Connor, B., Dyer, C., Gimpel, K., Schneider, N., & Smith, N. A. (2013). Improved part-of-speech tagging for online conversational text with word clusters. In Proceedings of NAACL-HLT (pp. 380-390).
34. Pedregosa F., Varoquaux G., Gramfort A., Michel V., Thirion B., Grisel O., et al. Scikit-learn: Machine learning in Python. Journal of Machine Learning Research 2011, 12:2825-2830.
35. Pew Trends in American values 1987-2012: Partisan polarization surges in Bush, Obama years 2012, The Pew Research Center for People & the Press, Washington, D.C.
36. Poole K.T., Rosenthal H. A spatial model for legislative roll call analysis. American Journal of Political Science 1985, 29:357-384.
37. Sang E.T.K., Bos J. Predicting the 2011 Dutch senate election results with Twitter. Proceedings of the workshop on semantic analysis in social media 2012, 53-60. Association for Computational Linguistics.
38. Scherer M. Inside the secret world of the data crunchers who helped Obama win. Time 2012, 7 November.
39. Scheufele D.A. Agenda-setting, priming, and framing revisited: Another look at cognitive effects of political communication. Mass Communication and Society 2000, 3(2-3):297-316.
40. Scheufele D.A., Tewksbury D. Framing, agenda setting, and priming: The evolution of three media effects models. Journal of Communication 2007, 57(1):9-20.
41. Smith, A. (2009). The internet's role in campaign 2008. Pew Internet and American Life Project, 15.
42. Stephens-Davidowitz, S. (2013). The cost of racial animus on a black presidential candidate: Using Google search data to find what surveys miss. Working paper, Harvard University.
43. Tumasjan A., Sprenger T., Sandner P., Welpe I. Election forecasts with Twitter: how 140 characters reflect the political landscape. Social Science Computer Review 2010.
44. Van Der Laan M., Polley E., Hubbard A. Super learner. Statistical Applications in Genetics and Molecular Biology 2007, 6(1):25.
45. Vance A. Facebook: The making of 1 billion users. Bloomberg BusinessWeek 2012, 4 October.
46. Viera L., Medway R.L., Turner S.R., Marsh S.M. Mail as an alternative to random-digit dial in a survey of young adults. Survey Practice 2013, 4(1).
47. Wallsten K. "Yes we can": How online viewership, blog discussion, campaign statements, and mainstream media coverage produced a viral video phenomenon. Journal of Information Technology and Politics 2010, 7(2-3):163-181.
48. Wang W., Rothschild D., Goel S., Gelman A. Forecasting elections with non-representative polls. International Journal of Forecasting 2015, 31(3):980-991.
49. Williamson V., Skocpol T., Coggin J. The Tea Party and the remaking of Republican conservatism 2011, Cambridge Univ. Press.
50. Wilson R.E., Gosling S.D., Graham L.T. A review of Facebook research in the social sciences. Perspectives on Psychological Science 2012, 7(3):203-220.