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arXiv · 2605.24307

Modernizing User Privacy Preference Measurement through GPPI: A GDPR-aligned Privacy Preference Item Bank

Yahya Hmaiti·Mykola Maslych·Amirpouya Ghasemaghaei·Trung Cuong Dang·Corey Pittman·David Mohaisen·Joseph J. LaViola Jr
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Abstract

Privacy measurement instruments (e.g., CFIP, IUIPC, PAQ) predate GDPR by over a decade and measure privacy concerns, distinct from preferences for regulatory protections (e.g., data portability, erasure, automated decision-making rights). This leaves practitioners without tools to assess whether users value the GDPR mechanisms implemented in compliant policies. We developed a GDPR-grounded privacy preference measurement item bank by extracting 669 statements from all 99 GDPR articles, validated by: (1) two-round expert review achieving full consensus on accuracy, (2) semantic clustering into 10 parent themes and 87 subthemes, and (3) consensus review with 50 privacy experts (5 per theme) using a larger or equal than 4/5 vote retention threshold. The final 527-item bank comprises 9 parent themes and 73 subthemes (18 to 112 items per parent theme, 1 to 29 per subtheme), enabling targeted measurement across granularities while covering GDPR at mean pairwise expert agreement of approx. 85%. This work introduces a complementary measurement dimension aligning user preferences with regulatory mechanisms.

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Yahya Hmaiti, Mykola Maslych, Amirpouya Ghasemaghaei, Trung Cuong Dang, Corey Pittman, David Mohaisen, Joseph J. LaViola Jr. 2026-05-23. Modernizing User Privacy Preference Measurement through GPPI: A GDPR-aligned Privacy Preference Item Bank. https://arxiv.org/abs/2605.24307

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