English

Does Ad-Free Mean Less Data Collection? An Empirical Study of Platform Data Practices and User Expectations

Computers and Society 2026-02-03 v1

Abstract

Online platforms increasingly offer "paid" ad-free subscriptions as an alternative to the traditional "free" ad-based model. The transition to ad-free models ostensibly removes advertising as a key justification for data processing under the GDPR. So, normatively, platforms should collect less user data. However, platforms may justify continued data collection as a means to provide an improved, personalized experience. This tension between privacy principles and platform incentives raises a critical underexplored question: do data collection practices vary between ad-free and ad-based subscription models? In this paper, we shed light on this important privacy issue by investigating the alignment between platform data collection practices and related user expectations. With respect to data collection process, our analyses of data exports from three major online platforms - Instagram, Facebook, and X - reveal that these platforms continue to retain or collect some ad-related data, even in ad-free subscriptions. With respect to user expectations, our survey among 255 participants on Prolific reveals that 69% of the participants normatively expect data collection to be reduced, indicating their expectation of improved digital privacy in an ad-free model. However, when asked what they think actually happens, 63% of these participants believed that platforms would still collect about the same amount of data, highlighting skepticism about platform practices. Our findings not only indicate a significant disconnect between data practices and normative user expectations, but also raise serious questions about platform compliance with core GDPR principles, such as purpose limitation, data minimization, and transparency.

Keywords

Cite

@article{arxiv.2602.01231,
  title  = {Does Ad-Free Mean Less Data Collection? An Empirical Study of Platform Data Practices and User Expectations},
  author = {Sepehr Mousavi and Abhisek Dash and Savvas Zannettou and Krishna P. Gummadi},
  journal= {arXiv preprint arXiv:2602.01231},
  year   = {2026}
}

Comments

This paper has been accepted at The ACM Web Conference 2026

R2 v1 2026-07-01T09:30:13.371Z