GOR 26 - Annual Conference & Workshops
Annual Conference- Rheinische Hochschule Cologne, Campus Vogelsanger Straße
26 - 27 February 2026
GOR Workshops - GESIS - Leibniz-Institut für Sozialwissenschaften in Cologne
25 February 2026
Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
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Session Overview |
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10.2: Data donation
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Data donations in online panels: Factors influencing donation probability 1GESIS - Leibniz Intitute for the Social Sciences, Germany; 2Utrecht University Relevance & Research Question Methods & Data Results In general, donation probabilities varied largely across studies and were strongly influenced by study design and contextual factors, such as donation method, the requested data type, and the recruitment strategy. Studies with a lower mean age generally showed higher donation probabilities. However, online panels displayed more consistent donation probabilities compared to cross-sectional recruitments. Potential moderating factors, such as participants’ familiarity with online data collections and trust in the institution receiving the donation, warrant further consideration. Added Value Motivations, Privacy, and Data Types: What Drives WhatsApp Chat Data Donation in a Probability Sample?” 1GESIS, Germany; 2University of Mannheim, Germany; 3University of Michigan, USA Relevance & Research Question Data donations are increasingly discussed as a valuable source for social science research. However, little probability-based evidence exists on what drives individuals’ hypothetical willingness to donate personal communication data. We examine three components that could influence consent behavior: motivational framing (societal benefit, personal benefit, no benefit information), privacy (consent from chat partners required vs. consent not required), and the requested data type (aggregated metadata vs. full chat content). Methods & Data The study was fielded in the May 2025 wave of the German Internet Panel (GIP), a probability-based online panel of the German adult population. Respondents were randomly assigned to one of 18 conditions in a 3×2×2 experimental design. The dependent variable was a binary measure of hypothetical willingness to donate WhatsApp chats, and we controlled for characteristics such as WhatsApp usage intensity and perceived data sensitivity. Overall, 11% of respondents (approx. 350 individuals) reported willingness to donate their chat data. Willingness was higher when societal benefit was emphasized (13%) compared with personal benefit or no benefit information (each 10%). Requiring consent from chat partners showed no significant effect (12% vs. 10%). Participants were more willing to donate when full chat content was requested (15%) rather than aggregated metadata (8%). Multivariate analyses indicated that willingness increased among heavy WhatsApp users and decreased with higher perceived data sensitivity. No significant interaction effects across experimental factors were found. Added Value This study provides one of the first probability-based examinations of willingness to donate WhatsApp chat data—an especially sensitive and understudied data type. The results indicate that, in this hypothetical context, variation in content sensitivity influenced stated willingness less than expected..These findings offer empirically grounded guidance for implementing future data donation infrastructures and highlight which informational cues and design choices may reduce barriers, increase trust, and support responsible integration of chat-based digital trace data into social research. For example, trying to limit the content sensitivity of a data donation request may not be as promising to increase data donation rates as simply emphasizing the research’s societal benefit. Motivate and persuade: Testing strategies to increase participation in data donation studies 1University of Mannheim, Germany; 2Institute for Employment Research, Germany; 3University of Klagenfurt, Austria; 4LMU Munich, Germany Relevance & Research Question Methods & Data Results Added Value | ||