Beyond Privacy Labels: How Users Perceive Different Information Sources for Understanding App's Privacy Practices

2026-02-22

AI Summary

Current privacy policies are often lengthy and opaque, while privacy labels tend to oversimplify and misrepresent data practices, leaving users unable to effectively understand how their data is handled. This work proposes a novel paradigm that integrates multiple information sources—privacy policies, user reviews, and community-based privacy assessments—to overcome the limitations of relying solely on labels and better accommodate users’ diverse privacy literacy and needs. Through a user study, we evaluate the perceived usefulness and trustworthiness of these sources and uncover how individual experiences shape these perceptions. Our findings reveal significant inter-individual differences in how users assess and trust different information sources, underscoring the importance of a multi-source, synergistic disclosure mechanism to enhance user comprehension and support informed privacy decisions.

Technology Category

• Machine Learning: Privacy
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy
• Application Domains: Humanities & Computational Social Science

Application Category

• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Security and Privacy: Privacy-enhancing technologies
• Responsible Web: Data and user privacy-enhancing technologies for the Web

Abstract

Despite having growing awareness and concerns about privacy, technology users are often insufficiently informed of the data practices of various digital products to protect themselves. Privacy policies and privacy labels, as two conventional ways of communicating data practices, are each criticized for important limitations -- one being lengthy and filled with legal jargon, and the other oversimplified and inaccurate -- causing users significant difficulty in understanding the privacy practices of the products and assessing their impact. To mitigate those issues, we explore ways to enhance privacy labels with the relevant content in complementary sources, including privacy policy, app reviews, and community-curated privacy assessments. Our user study results indicate that perceived usefulness and trust on those information sources are personal and influenced by past experience. Our work highlights the importance of considering various information needs for privacy practice and consolidating different sources for more useful privacy solutions.

Problem

• privacy labels
• privacy policies
• user perception
• information sources
• data practices

Innovation

• privacy labels
• information sources
• user perception
• privacy communication
• multi-source integration