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Photo Credit: Zac Freeland/Vox
Project | 01
Using Protection Motivation Theory and the Watchful Eye Effect to Understand Digital Upstander Behavior (published in Computers in Human Behavior)

Mobile phones have evolved to allow individuals to easily access and disclose the private information of others to a seemingly infinite network. Notably, the permanent nature of mobile data has aided its path between individuals and the police, storing integral evidence for criminal investigations in the palms of peoples' hands. Understanding cognitive factors that predict when an individual would choose to report mobile data to the police is pertinent, particularly in a time of heightened controversy over data access limits and ubiquitous surveillance. This study extends Protection Motivation Theory (PMT) through incorporating the watchful eye effect and the theory of contextual integrity to analyze predictors of intention to share data with the police. The results of a 2 (Situational severity: high or low) x 2 (Surveillance: present or absent) between-subjects factorial vignette methodology (N = 222) revealed that participants behaved independently of feeling watched, but that such sharing can be causally attributed to situational severity. Further, we found PMT variables—including perceived severity, response-efficacy, self-efficacy, and response cost—as well as perception of the police to serve as predictors of intentions to share with the police, with some of these factors mediating the effects of situational severity and surveillance. This study not only provides a theoretical contribution to PMT but also practical recommendations for mobile design that considers surveillance normalization and prioritizes data autonomy.

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Project | 02
Let's Talk About Facial Recognition Technology: How Framing and Context Influence Privacy Concern and Support for Policy​ (published in Telematics & Informatics)

Personal privacy has become increasingly compromised to allow for surveillance by both the government and private corporations. Specifically, the use of facial recognition technology (FRT) has become a point of contention and debate across the United States; in fact, a number of cities across the country have placed moratoriums on the public use of FRT until further research is done to confirm its accuracy and effectiveness. Using framing theory and the theory of contextual integrity, this study seeks to understand how both framing and context affect support for FRT policy and FRT privacy concerns. Through an online experimental survey of the youngest generation of voters (N = 150), a 2(Framing: episodic or thematic) x 2(Context: public or private) mixed factorial design was used to evaluate the aforementioned measures. Results from this study provide a theoretical contribution and emphasize the practical importance of strategically selecting the use of frames and context in FRT policy messaging.

Photo Credit: Boston Globe
Project | 03
An exploratory analysis of interface features influencing consent decisions on mobile location-based services (Under review)

Mobile location-based services (LBS) often ask users to consent to over disclose location data in exchange for their service. This online experiment manipulated interface features within an LBS consent screen to understand their independent and interactive influence on location data obscurity decisions. Participants (N  = 502) were led to believe they were involved in a location-tracking study, allowing for revealed preferences in their decisions. Results indicate that social proof and willingness-to-accept framing positively influenced participants' likelihood to obscure their location data. While the presence of friction and defaults had no direct effect, both interacted with other interface features in influencing decision-making.  

Project | 04
Photo Credit: Top Class Actions
Policy by Us For Them: Regulating Children’s Usage on TikTok (In Progress)

This study leverages the third person effect (TPE) and privacy calculus theory to understand the network of discourse surrounding childrens’ usage of TikTok. In particular, we are interested in how the effects on children are perceived by people who do not identify as that social class (i.e., adults). This study sheds light on how platform policy may be heavily influenced by TPE — that is, the perception of external third parties rather than the direct effects on children themselves. Results map a network of actors within the Twitter discourse onto attributed responsibility and privacy calculus of childrens’ TikTok use. Implications about how platforms make policy for other vulnerable populations on the basis of external opinion are discussed.

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