Vergara-Perucich, F. Assessing the Accuracy of Google Trends for Predicting Presidential Elections: The Case of Chile, 2006–2021. Data2022, 7, 143.
Vergara-Perucich, F. Assessing the Accuracy of Google Trends for Predicting Presidential Elections: The Case of Chile, 2006–2021. Data 2022, 7, 143.
Vergara-Perucich, F. Assessing the Accuracy of Google Trends for Predicting Presidential Elections: The Case of Chile, 2006–2021. Data2022, 7, 143.
Vergara-Perucich, F. Assessing the Accuracy of Google Trends for Predicting Presidential Elections: The Case of Chile, 2006–2021. Data 2022, 7, 143.
Abstract
This article presents the results of reviewing the predictive capacity of Google trends for national elections in Chile. The electoral results of the elections between Michelle Bachelet and Sebastián Piñera in 2006, Sebastián Piñera and Eduardo Frei in 2010, Michelle Bachelet and Evelyn Matthei in 2013, Sebastián Piñera and Alejandro Guillier in 2017, and Gabriel Boric and José Antonio Kast in 2021 were reviewed. The time series analysed were organised on the basis of relative searches between the candidacies, assisted by R software, mainly with the gtrendsR and forecast libraries. With the series constructed, forecasts were made using the ARIMA technique to check the weight of one presidential option over the other. The ARIMA analyses were performed on 3 ways of organising the data: the linear series, the series transformed by moving average and the series transformed by Hodrick-Prescott. The result indicates that the method offers optimal pre-dictive ability.
Keywords
elections; time series; forecasting; Chile; ARIMA
Subject
Social Sciences, Political Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
