I strongly believe in the value of openness and transparency in science. In light of recent meta-scientific discoveries (e.g., replication crisis, questionable research practices, etc.), I strongly advocate for making all materials (e.g., items, stimuli, coding procedures, etc.), data (if possible), and analysis scripts available to the public. I believe this is important not only for evaluating the study’s contribution and methodological soundness, but also to allow other researchers to reproduce this study’s results, replicate it independently, or use it in meta-analyses. In the last years, I have published several datasets that may be used for scientific purposes. If you have any questions about the data or are interested in collaborating on an analysis, please feel free to reach out.
Datasets focusing on Privacy and Self-Disclosure
- Trepte, S., Masur, P. K. & Dienlin, T. (2019). A longitudinal survey on privacy concerns, literacy, disclosure, support. (5 waves, representative for the German population). GESIS Datorium: https://datorium.gesis.org/xmlui/handle/10.7802/1937
- Masur, P. K. & Scharkow, M. (2016). A cross-sectional survey on privacy and self-disclosure on social media. Open Science Framework: https://osf.io/8bzxd/
- Bauer, A., Loy, L. S., Masur, P. K. & Schneider, F. M. (2018). A diary study on instant messaging and mindfulness. Open Science Framework: https://osf.io/nmf27/