Dana Turjeman’s research while affiliated with Reichman University and other places

Early in the new coronavirus disease (COVID-19) pandemic, scholars and journalists noted partisan differences in behaviors, attitudes, and beliefs. Based on location data from a large sample of smartphones, as well as 13,334 responses to a proprietary survey spanning 10 months from April 1, 2020 to February 15, 2021, we document that the partisan gap has persisted over time and that the lack of convergence occurs even among individuals who were at heightened risk of death. Our results point to the existence and persistence of the interaction of partisanship and information acquisition and highlight the need for mandates and targeted informational campaigns towards those with high health risks.

This paper investigates users’ reactions to a massive and highly sensitive data breach via an array of causal inference methodologies.

COVID-19 exposure-notification apps have struggled to gain adoption. Existing literature posits as potential causes of this low adoption: privacy concerns, insufficient data transparency, and the type of appeal used to pitch the pro-social behavior of installing the app. In a field experiment,we advertised CovidDefense, Louisiana's COVID-19 exposure-notification app, at the time it was released. We find that all three hypothesized factors -- privacy, data transparency, and appeals framing -- relate to app adoption, even when controlling for age, gender, and community density. Specifically, we find that collective-good appeals are effective in fostering pro-social COVID-19 app behavior in the field. Our results empirically support existing policy guidance on the use of collective-good appeals and offer real-world evidence in the on-going debate on the efficacy of such appeals. Further, we offer nuanced findings regarding the efficacy of transparency -- about both privacy and data collection -- in encouraging health technology adoption and pro-social COVID-19 behavior. Our results may aid in fostering pro-social public-health-related behavior and for the broader debate regarding privacy and data transparency in digital healthcare.

We create troves of data with nearly every step we take, every button we click, and every query we submit. These data can be used to cater to us with services that better align with our desires. They can help us locate restaurants matching our tastes, build up social networks with individuals sharing similar characteristics, find a soul mate or distant relative, attain financial goals, detect our health conditions, and potentially assist in developing individualized medicine. However, misuse of the data can induce us to buy things we don't need, offer us things that might harm our health, lead to an addiction, or even imprison us in the absence of wrongdoing. These data might also be breached, causing harm to us and our loved ones with revelations we might have never shared with the world. In this dissertation, in a series of three chapters, I detect opportunities and propose approaches to reduce the potential risks and leverage the benefits of data collection and data usage. I first analyze users' reactions to the data breach in a matchmaking website, exploring their engagement changes and potentially insufficient behaviors in privacy protection following the breach. I then plot how years of data collection in the Marketing realm and other business domains have led to great improvements to our lives, but have also introduced harms -- some of which are are still likely awaiting revelation. I discuss potential avenues for improving the benefits of the vast data we all create, while reducing the risks associated with those data. Finally, I explicitly develop one of these solutions -- a privacy preserving data fusion methodology -- intended to securely combine datasets while reducing the risks of de-identification. This dissertation, I hope, will serve as a steppingstone towards making the Marketing domain a safer zone in terms of privacy preservation. Marketing efforts were a major driver towards vast data collection and the associated benefits and harms; the marketing domain can now drive the efforts to further improve the benefits and reduce those harms.