Linking Surveys and Digital Trace Data: Insights From two Studies on Determinants of Data Sharing Behaviour

Abstract

Combining surveys and digital trace data can enhance the analytic potential of both data types. We present two studies that examine factors influencing data sharing behaviour of survey respondents for different types of digital trace data: Facebook, Twitter, Spotify and health app data. Across those data types, we compared the relative impact of four factors on data sharing: data sharing method, respondent characteristics, sample composition and incentives. The results show that data sharing rates differ substantially across data types. Two particularly important factors predicting data sharing behaviour are the incentive size and data sharing method, which are both directly related to task difficulty and respondent burden. In sum, the paper reveals systematic variation in the willingness to share additional data which need to be considered in research designs linking surveys and digital traces.

Determinants of willingness to donate data from social media platforms

“…Many empirical findings have already proved the effectiveness of monetary incentives in motivating people in research participation, such as responding to web surveys (see Göritz, 2006 for a meta-analysis or Keusch, 2015 for a review), and sharing digital trace data (Keusch et al, 2019;Silber et al, 2022). The results of Silber et al (2022) have shown that providing monetary incentives can have a positive effect on the willingness to share social media data.…”

“…1 In contrast, Jäckle et al (2019) and Beuthner et al (2023) found no effect of incentives on downloading an app or sharing different types of data. Silber et al (2022) also reported that incentives do not necessarily motivate all types of data-sharing (e.g., it does not work in the case of sharing highly sensitive health data).…”

“…In the case of data donation, little is known about the optimal amount and method of offering incentives. Too high incentives may make respondents suspicious and assume that their data is highly valuable, and eventually decrease their likelihood of participation (Silber et al, 2022).…”

“…Nevertheless, data donation is more burdensome compared to other, passive modes of data sharing (Keusch et al, 2019;Silber et al, 2022), since participants are required to actively download their data or even install a software for processing purposes, and then share it with the researchers. While data donation holds great promise to study online human behavior and some recent studies reported promising results (Baumgartner et al, 2022;Breuer et al, 2022;Kmetty & Bozsonyi, 2022;Kmetty & Németh, 2022), little is known about how to best optimize such approaches.…”

“…As a contribution to the literature, this study aims to understand the underlying mechanisms of the willingness to participate in academic research as a social media data donor. Earlier research has shown that digital data-sharing behavior in a broader sense can be a function of the offered incentives (Jäckle et al, 2019;Keusch et al, 2019;Ságvári et al, 2021), the type of data (Beuthner et al, 2023;Revilla et al, 2019;Silber et al, 2022;Wenz et al, 2019) (Revilla et al, 2019;Silber et al, 2022;Wenz et al, 2019, Beuthner 2023, the autonomy over data collection or the study's sponsor (Keusch et al, 2019;Struminskaya et al, 2020Struminskaya et al, , 2021, (Keusch et al, 2019;Struminskaya et al, 2020), the respondents' characteristics such as privacy concerns (Struminskaya et al, 2021), and various other factors as well.…”