Maximizing Data Yield - An Experimental Study of Framing and Motivation in Data Donation

Utrecht
,
2025

Keusch, Florian, Frieder Rodewald, Valerie Hase, Frauke Kreuter, Mark Trappmann

Data protection regulations in the EU, Brasil, and California give users the right to access the information online platforms hold about them. Data donation studies capitalize on this legal requirement by asking web survey respondents to donate their data at the end of the survey. This sequential approach assumes that respondents' prior engagement with the survey enhances their willingness to donate data. However, this approach often results in modest donation rates. An alternative approach is to directly frame the study in the context of a data donation task, thus increasing the commitment to provide additional data at the end of the survey. In this study, we conduct a 2x3 experiment involving over 2,000 participants from a German online access panel. Panel members are invited to a study framed (1) as a web survey introducing data donation only once respondents completed the questionnaire or (2) as a data donation study from the beginning. When asked for data donation, we also randomly vary the appeal (1) emphasizing participants' ability to quantify their online platform behavior, (2) emphasizing participants' ability to learn what online platforms know about them, and (3) no appeal. We ask for data donations from YouTube, Instagram, and LinkedIn. Our hypotheses posit that while initial study participation rates will be higher for the survey framing than for the data donation framing, participants' willingness to donate will be significantly higher for those in the data donation framing. Further emphasizing the personal benefits of the data donation should increase the willingness to donate compared to having no such emphasis, especially when presented at the study's start rather than the end. We also examine how the framing influences sample composition, specifically regarding technical skills, self-monitoring openness, frequency of platform usage, privacy concerns, and trust in a platform.