While survey research has been at the heart of social science for decades and social scientific research with digital trace data has been growing rapidly in the last few years, until now, there are relatively few studies that combine these two data types. This may be surprising given the potential of linking surveys and digital trace data, but at the same time, it is important to note that the collection and analysis of such linked data are challenging in several regards. The three key issues are: (1) data linking including informed consent for individual-level studies, (2) methodological and ethical issues impeding the scientific (re)analysis of linked survey and digital trace data sets, and (3) developing conceptual and theoretical frameworks tailored toward the multidimensionality of such data. This special issue addresses these challenges by presenting cutting-edge methodological work on how to best collect and analyze linked data as well as studies that have successfully combined survey data and digital trace data to find innovative answers to relevant social scientific questions.

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The question of whether religiosity is linked to prosocial behavior is currently hotly debated in psychology. This research contributes to this debate by showing that the nature of individuals' religious orientations and their relationships to prosociality depend on their country's social enforcement of religiosity. Our analyses of data from more than 70 countries indicate that in countries with no social pressure to follow a religion, religious individuals are more likely to endorse an intrinsic religious orientation (Study 1), engage in charity work (Study 2), disapprove of lying in their own interests (Study 3), and are less likely to engage in fraudulent behaviors (Study 4) compared with non-religious individuals. Ironically, in secular contexts, religious individuals are also more likely to condemn certain moral choices than non-religious individuals (Study 2). These effects of religiosity substantially weaken (and ultimately disappear) with increasing national levels of social enforcement of religiosity.

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.

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