Harnessing the Potential of Google Searches for Understanding Dynamics of Intimate Partner Violence Before and After the COVID-19 Outbreak

Selin Köksal (), Luca Maria Pesando (), Valentina Rotondi and Ebru Şanlıtürk ()
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Selin Köksal: Bocconi University
Luca Maria Pesando: McGill University
Ebru Şanlıtürk: Max Planck Institute for Demographic Research

European Journal of Population, 2022, vol. 38, issue 3, No 8, 517-545

Abstract: Abstract Most social phenomena are inherently complex and hard to measure, often due to under-reporting, stigma, social desirability bias, and rapidly changing external circumstances. This is for instance the case of Intimate Partner Violence (IPV), a highly-prevalent social phenomenon which has drastically risen in the wake of the COVID-19 pandemic. This paper explores whether big data—an increasingly common tool to track, nowcast, and forecast social phenomena in close-to-real time—might help track and understand IPV dynamics. We leverage online data from Google Trends to explore whether online searches might help reach “hard-to-reach” populations such as victims of IPV using Italy as a case-study. We ask the following questions: Can digital traces help predict instances of IPV—both potential threat and actual violent cases—in Italy? Is their predictive power weaker or stronger in the aftermath of crises such as COVID-19? Our results suggest that online searches using selected keywords measuring different facets of IPV are a powerful tool to track potential threats of IPV before and during global-level crises such as the current COVID-19 pandemic, with stronger predictive power post outbreaks. Conversely, online searches help predict actual violence only in post-outbreak scenarios. Our findings, validated by a Facebook survey, also highlight the important role that socioeconomic status (SES) plays in shaping online search behavior, thus shedding new light on the role played by third-level digital divides in determining the predictive power of digital traces. More specifically, they suggest that forecasting might be more reliable among high-SES population strata.

Keywords: Digital data; Google Trends; Intimate partner violence; Facebook survey; Italy; COVID-19 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10680-022-09619-2

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