Predicting Elections for Multiple Countries Using Twitter and Polls
Open accessAbstract
The authors' work focuses on predicting the 2014 European Union elections in three different countries using Twitter and polls. Past works in this domain relying strictly on Twitter data have been proven ineffective. Others, using polls as their ground truth, have raised questions regarding the contribution of Twitter data for this task. Here, the authors treat this task as a multivariate time-series forecast, extracting Twitter- and poll-based features and training different predictive algorithms. They've achieved better results than several past works and the commercial baseline.
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Cites
Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment
Tumasjan, A., Sprenger, T. O., Sandner, P., & Welpe, I. M. (2010) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v4i1.14009 · Cited by 2,647 · see citing works
From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series
O'Connor, B., Balasubramanyan, R., Routledge, B., & Smith, N. A. (2010) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v4i1.14031 · Cited by 1,922 · see citing works
Is the Sample Good Enough? Comparing Data from Twitter's Streaming API with Twitter's Firehose
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How (Not) to Predict Elections
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A user-centric model of voting intention from Social Media
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Flagged first, then by citations
Research works printed but not linked: 1
- Lei Shi, Neeraj Agarwal, Ankur Agrawal, Rahul Garg, and Jacob Spoel- stra. Predicting us primary elections with twitter. In Proceedings of Social Network and Social Media Analysis: Methods, Models and Ap- plications (NIPS Workshop), Lake Tahoe, NV, December, volume 7, 2012.
Cited by
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DNA-Inspired Online Behavioral Modeling and Its Application to Spambot Detection
Cresci, S., Di Pietro, R., Petrocchi, M., Spognardi, A., & Tesconi, M. (2016) · IEEE Intelligent Systems · doi:10.1109/mis.2016.29 · Cited by 194 · see citing works
“One is to mine substantial information regarding events of public interest [1].”
Background
- Authors
- Tsakalidis, A., Papadopoulos, S., Cristea, A. I., & Kompatsiaris, Y.
- Affiliations
- University of Warwick (GB)
- Information Technologies Institute (GR)
- Venue
- IEEE Intelligent Systems
- Published
- 2015-03
- Volume
- 30
- Issue
- 2
- Pages
- 10-17
- ISSN
- 1541-1672 (ISSN-L)
- OpenAlex
- W2060747203
- Cited by
- 79
- References
- 10
- Citations by year
- 2026: 4 · 2025: 2 · 2024: 1 · 2023: 3 · 2022: 6 · 2021: 11 · 2020: 14 · 2019: 11 · 2018: 13 · 2017: 5 · 2016: 7 · 2015: 2
- FWCI
- 11.25
- Type
- journal article
- Language
- en
- Open access
- green
- dro.dur.ac.uk
- Locations
- IEEE Intelligent Systems (publishedVersion)
- Warwick Research Archive Portal (University of Warwick) (acceptedVersion)
- Durham Research Online (Durham University) (submittedVersion, cc-by)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
- Social Sciences › Decision Sciences › Management Science and Operations Research › Stock Market Forecasting Methods
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Keywords
- election forecasting, 2014 European Parliament elections, Twitter, public opinion survey, multivariate time series forecasting, feature extraction, predictive algorithms
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