Willingness to link digital behavioral data in surveys
The widespread use of digital technologies including smartphones, wearables, and other IoT-devices produce a plethora of digital behavioral data about how people interact with online systems but also about their behaviors and social interactions in the real world (e.g., physical activity, health, mobility). The transformative potential of digital technologies in data collection allows researchers to go beyond traditional survey methods and incorporate additional sources to enhance the richness of datasets in the social sciences. However, low willingness of individuals to link and share digital behavioral data with data from self-reports limits its current application due to concerns about bias.
Ethical considerations and obtaining informed consent emerges as one significant challenge in the utilization of digital behavioral data. In a series of papers we highlight the importance of respecting respondents' privacy concerns and legal obligations, especially when linking sensitive data domains. We systematically explor factors that influence individuals' consent rates, such as question wording, incentives, and contextual elements and offer practical guidance for researchers aiming to improve consent rates in data linkage procedures.
The project also underscore the limitations of self-reports, particularly in areas like social media usage, and advocate for the integration of more objective digital trace data. The studies address various methods for collecting such data, including the challenges associated with API restrictions, privacy concerns related to device trackers, and the relatively unexplored terrain of data donation.
Collaborators: Ruben L. Bach, Alexandru Cernat, Paulina Pankowska, Jette Schröder, Henning Silber
Publications:
Ethical considerations and obtaining informed consent emerges as one significant challenge in the utilization of digital behavioral data. In a series of papers we highlight the importance of respecting respondents' privacy concerns and legal obligations, especially when linking sensitive data domains. We systematically explor factors that influence individuals' consent rates, such as question wording, incentives, and contextual elements and offer practical guidance for researchers aiming to improve consent rates in data linkage procedures.
The project also underscore the limitations of self-reports, particularly in areas like social media usage, and advocate for the integration of more objective digital trace data. The studies address various methods for collecting such data, including the challenges associated with API restrictions, privacy concerns related to device trackers, and the relatively unexplored terrain of data donation.
Collaborators: Ruben L. Bach, Alexandru Cernat, Paulina Pankowska, Jette Schröder, Henning Silber
Publications:
- Keusch, F., Pankowska, P., Cernat, A., & Bach, R. (2024). Do you have two minutes to talk about your data? Willingness to participate and nonparticipation bias in Facebook data donation. Field Methods. Published online before print, January 11, 2024. 10.1177/1525822X231225907
- Beuther, C., Weiß, B., Silber, H., Keusch, F., & Schröder, J. (2023). Consent to data linkage for different data domains – The role of question order, question wording, and incentives. International Journal of Social Research Methodology. Published online before print, February 6, 2023. 10.1080/13645579.2023.2173847
- Silber, H., Gerdon, F., Bach, R., Kern, C., Keusch, F., & Kreuter, F. (2022). A preregistered vignette experiment on determinants of health data sharing behavior: Willingness to donate sensor data, medical records, and biomarkers. Politics and the Life Sciences, 41, 161-181. 10.1017/pls.2022.15