The Community for Technology Leaders
RSS Icon
Issue No.06 - Nov.-Dec. (2012 vol.16)
pp: 91-94
Daniel Gayo-Avello , University of Oviedo, Spain
Predicting X from Twitter is a popular fad within the Twitter research subculture. It seems both appealing and relatively easy. Among such studies, electoral prediction is maybe the most attractive, and a growing body of literature exists on this topic. This research problem isn't only interesting, but is also extremely difficult. However, most authors seem to be more interested in claiming positive results than in providing sound and reproducible methods. It's also especially worrisome that recent papers seem to only acknowledge those studies supporting the idea that Twitter can predict elections. This is all problematic because while simple approaches are purported to be good enough, the predictive power of Twitter regarding elections has been greatly exaggerated, and difficult research problems still lie ahead.
Prediction methods, Voting, Twitter, elections, Twitter, social media, prediction, forecasting, politics
Daniel Gayo-Avello, "No, You Cannot Predict Elections with Twitter", IEEE Internet Computing, vol.16, no. 6, pp. 91-94, Nov.-Dec. 2012, doi:10.1109/MIC.2012.137
1. “Yahoo Search Tracks the Road to the White House,” blog, 30 Oct. 2008; /.
2. d. boyd, “Big Data: Opportunities for Computational and Social Sciences,” blog, 17 Apr. 2010; 04/17big-data-opportunities-for-computational-and-social-sciences.html .
3. D. Fanelli, “Do Pressures to Publish Increase Scientists' Bias? An Empirical Support from US States Data,” PLoS ONE, vol. 5, no. 4, 2010; journal.pone.0010271.
4. A. Tumasjan et al., “Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment,” Proc. 4th Int'l AAAI Conf. Weblogs and Social Media, AAAI Press, 2010, pp. 178–185.
5. B. O'Connor et al., “From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series,” Proc. Int'l AAAI Conf. Weblogs and Social Media, AAAI Press, 2010, pp. 122–129.
6. D. Gayo-Avello, “Don't Turn Social Media into Another 'Literary Digest' Poll,” Comm. ACM, vol. 54, no. 10, 2011, pp. 121–128.
7. P.T. Metaxas, E. Mustafaraj, and D. Gayo-Avello, “How (Not) to Predict Elections,” Proc. IEEE Int'l Conf. Privacy, Security, Risk, and Trust (PASSAT) and Int'l Conf. Social Computing (SocialCom), 2011, pp. 165–171.
8. A. Jungherr, P. Jürgens, and H. Schoen, “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 Rev., April 2011; 04/050894439311404119.abstract.
9. C. Castillo, M. Mendoza, and B. Poblete, “Information Credibility on Twitter,” Proc. 20th Int'l Conf. World Wide Web (WWW 11), ACM, 2011, pp. 675–684.
10. M.R. Morris et al., “Tweeting Is Believing? Understanding Microblog Credibility Perceptions,” Proc. 15th ACM Conf. Computer Supported Cooperative Work and Social Computing (CSCW 13), ACM, 2012, pp. 441–450.
18 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool