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Predicting elections for multiple countries using Twitter and polls

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Tsakalidis, Adam, Papadopoulos, S., Cristea, Alexandra I. and Kompatsiaris, Yiannis (2015) Predicting elections for multiple countries using Twitter and polls. IEEE Intelligent Systems, 30 (2). pp. 10-17. doi:10.1109/MIS.2015.17

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Official URL: http://dx.doi.org/10.1109/MIS.2015.17

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Abstract

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.

Item Type: Journal Article
Subjects: H Social Sciences > HA Statistics
J Political Science > JN Political institutions (Europe)
Divisions: Faculty of Science > Computer Science
Library of Congress Subject Headings (LCSH): Twitter (Firm) , European Union -- Elections, 2014 -- Germany, European Union -- Elections, 2014 -- Netherlands, European Union -- Elections, 2014 -- Greece, Election forecasting -- European Union , Exit polling (Elections) -- European Union , Public opinion polls -- European Union , Time-series analysis -- Elections, 2014 -- European Union
Journal or Publication Title: IEEE Intelligent Systems
Publisher: IEEE Computer Society
ISSN: 1541-1672
Official Date: March 2015
Dates:
DateEvent
26 January 2015Available
5 January 2015Accepted
March 2015Published
Volume: 30
Number: 2
Page Range: pp. 10-17
DOI: 10.1109/MIS.2015.17
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Funder: Seventh Framework Programme (European Commission) (FP7)
Grant number: 287975

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