The platform matters: cross-platform differences in data donation willingness, behavior, and bias

Data donations are a method to access user-level digital trace data, as they provide fine-grained measures of content exposure on social media. The interest in data donation as a data collection method is accompanied by a broad uncertainty about the reasons that drive the donation of data by users. The current literature lacks comparative analysis across various platforms. This study investigates platform-specific predictors for data donation behavior of a non-probability quota sample of German social media users (N = 2,296) for YouTube, Facebook, Instagram, and TikTok and the resulting non-response biases. Based on the analysis of 340 data donation packages, we find that participants are less likely to donate TikTok data compared to the other platforms. Gender is the main driver during the willingness step for drop offs, while political leaning is a key predictor for all platforms except Facebook during the donation stage. Data donors tend to self-report less active social media usage with news and political content than those who do not donate data. Our findings highlight the importance of considering platform-specific differences in expected donation rates, biases, and the potential for discrepancies between indicated willingness and actual donation behavior when designing and interpreting data donation studies.

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Publication Details

Journal
Communication Methods and Measures
Published
2025-12-27
DOI
https://doi.org/10.1080/19312458.2025.2605946
Primary Topic
Sharing Economy and Platforms
Type
article
Field-Weighted Citation Impact
0.00
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article

The platform matters: cross-platform differences in data donation willingness, behavior, and bias

Anna-Theresa Mayer, Jakob Ohme, Lion Wedel, Yangliu Fan et al.
Communication Methods and Measures
Sharing Economy and Platforms
article

The platform matters: cross-platform differences in data donation willingness, behavior, and bias

Anna-Theresa Mayer, Jakob Ohme, Lion Wedel, Yangliu Fan, Gaisbauer Felix
article en

Abstract

Data donations are a method to access user-level digital trace data, as they provide fine-grained measures of content exposure on social media. The interest in data donation as a data collection method is accompanied by a broad uncertainty about the reasons that drive the donation of data by users. The current literature lacks comparative analysis across various platforms. This study investigates platform-specific predictors for data donation behavior of a non-probability quota sample of German social media users (N = 2,296) for YouTube, Facebook, Instagram, and TikTok and the resulting non-response biases. Based on the analysis of 340 data donation packages, we find that participants are less likely to donate TikTok data compared to the other platforms. Gender is the main driver during the willingness step for drop offs, while political leaning is a key predictor for all platforms except Facebook during the donation stage. Data donors tend to self-report less active social media usage with news and political content than those who do not donate data. Our findings highlight the importance of considering platform-specific differences in expected donation rates, biases, and the potential for discrepancies between indicated willingness and actual donation behavior when designing and interpreting data donation studies.

Communication Methods and MeasuresVol. 20(1)
Weizenbaum Institute (DE), Freie Universität Berlin (DE)
Openalex Percentile: Top 28%
Sharing Economy and Platforms
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The platform matters: cross-platform differences in data donation willingness, behavior, and bias — Anna-Theresa Mayer, Jakob Ohme, et al. · Communication Methods and Measures (2025) | TGRS Research Map | TGRS