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

Author:
Camilo Prado-Román, Raúl Gómez-Martínez, Carmen Orden-Cruz
Source:
American behavioral scientist 2021 v.65 no.4 pp. 666-680
ISSN:
1552-3381
Subject:
scientists, statistics, Canada
Abstract:
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.
Agid:
7319044