Do search queries predict violence against women? A forecasting model based on Google Trends

Nicolás Gonzálvez‐Gallego, María Concepción Pérez‐Cárceles and Laura Nieto‐Torrejón

Journal of Forecasting, 2024, vol. 43, issue 5, 1607-1614

Abstract: This paper introduces a new indicator for reported intimate partner violence against women based on search query time series from Google Trends. This indicator is built up from the relative popularity of three topic‐related keywords. We propose a predictive model based on this specific Google index that is assessed relative to two alternative models: the first one includes the lagged variable, while the second one considers fatalities as a predictor. This comparative analysis is run in two different samples, whether the reported cases are a direct consequence of a violent direct or not. Our results show that the predictive model based on Google data significantly outperforms the other two models, regardless the sample and the forecast horizon. Then, using information gathered from Google queries may improve the allocation and management of resources and services to protect women against this form of violence and to improve risk assessment.

Date: 2024
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https://doi.org/10.1002/for.3102

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Persistent link: https://EconPapers.repec.org/RePEc:wly:jforec:v:43:y:2024:i:5:p:1607-1614

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