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

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

Working Paper Number
2022-61
Publication Year
2022
Authors
Selin Köksal
Luca Maria Pesando
Valentina Rotondi
Ebru Şanlıtürk
Paper 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 forecasting power of digital traces. More specifically, they suggest that forecasting might be more reliable among high-SES population strata.

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The Population Studies Center (PSC) at the University of Pennsylvania (Penn) was founded in 1962 and stands as an international leader in research and training on the dynamic structure, organization, and health and well-being of human populations. The services that PSC provides have been funded by infrastructure grants awarded by the Population Dynamics Branch at Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) since 1978. The center and its associates are also supported by research grants and contracts awarded by federal agencies including the National Institutes of Health and the National Science Foundation and by private foundations. Penn’s School of Arts and Sciences is the administrative home of the PSC and provides generous dedicated support to the center.

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