Framing Data Choices: How Pre-Donation Exploration Design Influence Data Donation Behavior and Decision-Making

2026-03-25

AI Summary

This study addresses the persistent gap between users’ willingness and actual behavior in data donation practices, focusing on how the presentation of personal data influences donation decisions—a dimension underexplored from a design-oriented perspective. Through a real-world experiment (N=24), the research evaluates three pre-donation data exploration frameworks: “self-focused,” “social comparison,” and “collective uniqueness.” Findings reveal that the “social comparison” frame significantly increases donation rates to 87.5%, outperforming the “self-focused” condition (62.5%), whereas the “collective uniqueness” frame reduces donations to 37.5% due to induced cognitive confusion and heightened privacy concerns. This work pioneers the integration of behavioral design into public-sector data donation, uncovering a pronounced framing effect in data selection and underscoring the critical role of interface design in fostering meaningful user participation.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Humans and AI: Intelligent User Interfaces
• Data Mining & Knowledge Management: Data Compression

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Responsible Web: Consent frameworks and practices on the web
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

Abstract

Data donation, an emerging user-centric data collection method for public sector research, faces a gap between participant willingness and actual donation. This suggests a design absence in practice: while promoted as "donor-centered" with technical and regulational advances, a design perspective on how data choices are presented and intervene on individual behaviors remain underexplored. In this paper, we focus on pre-donation data exploration, a key stage for adequately and meaningful informed participation. Through a real-world data donation study (N=24), we evaluated three data exploration interventions (self-focused, social comparison, collective-only). Findings show choice framing impacts donation participation. The "social comparison" design (87.5%) outperformed the "self-focused view" (62.5%) while a "collective-only" frame (37.5%) backfired, causing "perspective confusion" and privacy concerns. This study demonstrates how strategic data framing addresses data donation as a behavioral challenge, revealing design's critical yet underexplored role in data donation for participatory public sector innovation.

Problem

• data donation
• choice framing
• donor-centered design
• behavioral challenge
• public sector research

Innovation

• data donation
• choice framing
• pre-donation exploration
• behavioral design
• participatory innovation