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Citation |
Köksal S, Pesando LM, Rotondi V, Şanlıtürk E. Eur. J. Popul. 2022; ePub(ePub): ePub. |
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Copyright |
(Copyright © 2022, Holtzbrinck Springer Nature Publishing Group) |
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DOI |
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PMID |
35668864 |
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PMCID |
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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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10680-022-09619-2. Language: en |
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Keywords |
Italy; Intimate partner violence; COVID-19; Digital data; Facebook survey; Google Trends |