The project studies the impact of privacy interventions on the online publishing industry. Widespread concerns over online privacy have led governments worldwide to enact new privacy regulations and have compelled firms to implement self-regulatory data-protection initiatives. While such privacy interventions are often positively received by the public, industry stakeholders have suggested that privacy interventions may reduce the availability of free, ad-supported online content and services. Online publishers and their ability to provide content play a crucial role in democratic societies. The project integrates technical, organizational, behavioral, and economic studies to investigate how the implementation of privacy interventions impacts publishers, their users, and various downstream economic outcomes. The project aims at providing insights for scholars, policy makers, and practitioners toward understanding and designing effective privacy interventions without endangering digital products and services.
The project leverages collaborations with media companies granting access to data from a large set of heterogeneous websites. The novel contributions of the project include: 1) the investigation of factors influencing publishers? compliance with privacy interventions; 2) the creation of an open auditing API for automated remote compliance auditing of publishers? systems; 3) the analysis of users? responses to privacy mechanisms to understand the extent to which privacy initiatives translate into usable tools for users; 4) the investigation of the impact of privacy implementations on user engagement and experience; 5) the investigation of how the implementation of privacy initiatives affects publishers? revenues from online advertising; and 6) the investigation of how the gains from user data are allocated across the stakeholders in the online publishing ecosystem in the presence of privacy initiatives. The collaboration with media companies enables quick transfer of research findings to the industry. The results of the research are incorporated in courses on online privacy and its impact on publishers and society.
Lefrere, V., Warberg, L., Cheyre, C., Marotta, V., & Acquisti, A. (2024). Does Privacy Regulation Harm Content Providers? A Longitudinal Analysis of the Impact of the GDPR (April 1, 2024). Forthcoming Management Science https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4239013
Moradi, P., Cheyre, C., and Acquisti, A. (2025) Economic Rationales for Regulating Behavioral Ads. Forthcoming in Yale Law Journal of Law & Technology. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4954788
Smith, M., Torres-Agüero, A., Grossman, R., Sen, P., Chen, Y., and Borcea, C. (2024) A Study of GDPR Compliance under the Transparency and Consent Framework. Proceedings of the ACM Web Conference 2024 https://dl.acm.org/doi/abs/10.1145/3589334.3645618
Grossman, R., Smith, M., Borcea, C., and Chen, Y. (2026). Using Salient Object Detection to Identify Manipulative Cookie Banners that Circumvent GDPR. Forthcoming in International AAAI Conference on Web and Social Media (ICWSM) 2026. https://arxiv.org/abs/2510.26967
Alemari, A., Sen, P., and Borcea, C. (2026) AdFL: In-browser Federated Learning for Online Advertisement. To appear in International AAAI Conference on Web and Social Media (ICWSM 2026).
Smith, M., Torres-Agüero, A., Grossman, R., Sen, P., Borcea, C., and Chen, Y. (2024). Inconsistencies in Classification of Online News Articles: A Call for Common Standards in Brand Safety Services. Forthcoming in International AAAI Conference on Web and Social Media (ICWSM) 2026.
Sen, P. and Borcea, C. (2024) FedMTL: Privacy-Preserving Federated Multi-Task Learning. Proceedings of the 27th European Conference on Artificial Intelligence (ECAI), 2024. https://ebooks.iospress.nl/doi/10.3233/FAIA240715
Nguyen, K., Ton, T. K., Phan, N., Khalil, I., Tran, K., Borcea, C., Jin, R., Khreishah, A., and Thai, M. (2026) NOIR: Privacy-Preserving Generation of Code with Open-Source LLMs, To appear in the 35th Usenix Security Symposium (Usenix Security 2026), August 2026
Michael K. Chen, Shuai Zhao, Christian Borcea, Yi Chen. (2025) A Field Study on the Impact of the Counter Ad-Blocking Wall Strategy on User Engagement. Decision Support Systems, Volume 198, November 2025 https://www.sciencedirect.com/science/article/abs/pii/S0167923625001265
Grossman, R., Liu, S., Chen, M., Smith, M., Borcea, C., and Chen, Y. (2026) Discrepancies Between Traditional and AI-powered Search and Their Impact on the Web. Under submission
Smith, M., Grossman, R., Franaszek, K., Torres-Agüero, A., Borcea, C., Chen, Y. (2025). A Longitudinal Study of Extended User IDs in the Online Advertising Ecosystem. Under submission
Tobias Kircher, Riley Grossman, Mike Smith, Alessandro Acquisti, Cristian Borcea, Yi Chen, Cristobal Cheyre. (2026). Privacy Interventions and Publishers’ Revenues: The Role of Ad Spending Reallocation (2026). Working paper.
Cheyre, C., Leyden, B., Baviskar, S., & Acquisti, A. (2023). The Impact of Apple’s App Tracking Transparency Framework on the App Ecosystem (No. 10456). CESifo. (Invited second round Management Science)
Firullo C. & Cheyre C. (2024) The Cursed Equilibrium of Algorithmic Traumatization. Stanford Trust and Safety Conference.
Faculty :
Yi Chen < yi.chen@njit.edu >
Cristian Borcea < borcea@njit.edu >
Alessandro Acquisti < acquisti@mit.edu >
Cristobal Cheyre < cac555@cornell.edu >
Students :
Riley Grossman < rag24@njit.edu >
Mike Smith < mes6@njit.edu >
Pritam Sen < ps37@njit.edu >
Tobias Kircher < tobias.kircher@tum.de >
Ahmad Alemari <aaa376@njit.edu>
Songjiang Liu <sl947@njit.edu>
Michael K Chen <michaelchenkj@gmail.com>
Collaborators:
Antonio Torres (Deepsee.io)
This project is supported by the National Science Foundation under Grants No. CNS 2237327, CNS 2237328, and CNS 2237329.