2004
Volume 6, Issue 2
  • E-ISSN: 2665-9085

Abstract

The use of online media has led to an increase in digital footprints of human behavior, which has resulted in a growing interest in the collection and analysis of such data in non-intrusive ways. One such approach is digital data donation, which involves requesting participants to share data that they have requested from digital platforms with researchers. While this approach promises to provide an unprecedented level of detail for computational communication research, it also raises concerns about the representativeness and validity of the data. This study investigates the issue of potential selection bias and non-response bias in data donation samples. It aims to identify subparts of the population that might be underrepresented (or even absent) in data donation sampling methods, which might lead to inaccurate and biased research conclusions. Utilizing a survey with a sample frame of 1178 and 289 participants from the Netherlands, the study investigates the relation between demographics, knowledge, privacy and trust factors, and donation behavior. The results show biases in donation behavior in terms of age and digital and algorithmic efficacy, while privacy and trust factors are not related to it. It suggests that individuals decide not to donate to academic research due to skills and not due to concerns or lack of trust. This offers possibilities for improvement in study design so that all willing individuals are equally able to participate.

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