Google Trends as a Predictor of Presidential Elections: The United States Versus Canada

The media and election campaign managers conduct several polls in the days leading up to the presidential elections. These preelection polls have a different predictive capacity, despite the fact that under a Big Data approach, sources that indicate voting intention can be found. In this article, we...

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Bibliographic Details
Published inThe American behavioral scientist (Beverly Hills) Vol. 65; no. 4; pp. 666 - 680
Main Authors Prado-Román, Camilo, Gómez-Martínez, Raúl, Orden-Cruz, Carmen
Format Journal Article
LanguageEnglish
Published Los Angeles, CA SAGE Publications 01.04.2021
SAGE PUBLICATIONS, INC
Subjects
Big Data
Candidates
Election monitoring
Election results
Elections
Political campaigns
Polls & surveys
Predictions
Presidential elections
Presidents
Statistics
Voting
Canada
United States > US
Big Data
Google trends
elections
political strategies
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Summary:The media and election campaign managers conduct several polls in the days leading up to the presidential elections. These preelection polls have a different predictive capacity, despite the fact that under a Big Data approach, sources that indicate voting intention can be found. In this article, we propose a free method to anticipate the winner of the presidential election based on this approach. To demonstrate the predictive capacity of this method, we conducted the study for two countries: the United States of America and Canada. To this end, we analysed which candidate had the most Google searches in the months leading up to the polling day. In this article, we have taken into account the past four elections in the United States and the past five in Canada, since Google first published its search statistics in 2004. The results show that this method has predicted the real winner in all the elections held since 2004 and highlights that it is necessary to monitor the next elections for the presidency of the United States in November 2020 and to have more accurate information on the future results.
ISSN:0002-7642
1552-3381
DOI:10.1177/0002764220975067