Longitudinal Data Donation Behavior and Data Omission across Four Social Media Platforms

Abstract

This research article presents insights from a two-wave, longitudinal data donation study across four major social media platforms: TikTok, YouTube, Facebook, and Instagram. We investigate a critical yet underexplored aspect of data donation: allowing participants to delete specific data traces before submission. Our analysis quantifies the impact of this selective omission on data completeness and, consequently, the analytical power of the resulting datasets. Furthermore, leveraging a longitudinal design, we examine the stability of donation and deletion behaviors over time in a panel setting. Findings reveal an overall increase in the platform donor rate in the second wave. However, we also observe substantial donor attrition. Notably, the omission of data traces is predominantly observed among first-time donors.Our results suggest the feasibility of longitudinal data donation research designs. For allowing participants selective data omission, a careful weighing of the trade-offs is necessary, as this practice—when utilized—significantly compromises data completeness.