Large-scale, cross-national surveys in the social sciences are often conducted in person, making them costly and resource-intensive. Online surveys offer a faster and less expensive alternative, but they frequently face challenges related to representativeness and targeted participant recruitment. Advertising-based online survey recruitment has emerged as a promising methodological response. In this approach, researchers purchase advertisements on social media platforms, which appear in users’ feeds and invite them to participate in an online survey. Given the global reach of the online advertising industry, this method can facilitate the recruitment of comparatively diverse and cross-national samples.

The project brought together Dr Dennis Redeker from the ZeMKI, Centre for Media, Communication and Information Research at the University of Bremen, and data scientist Ingmar Sturm from the University of California, Santa Barbara. Through two collaborative workshops at the University of Bremen, the researchers worked on advancing advertising-based online recruitment through automation and optimisation. The first workshop focused on research and conceptual development. It aimed to establish a robust framework for the method and to draft an R package designed to automate this emerging sampling approach. The second workshop took the form of a training session for doctoral researchers from different disciplines at the University of Bremen. The seed grant also funded a student research assistant to support the project.

In the long term, the project seeks to help scale existing survey-based research at the University of Bremen through data science methods while reducing the resources required for large-scale empirical research.

Funding recipient: Dr Dennis Redeker, Faculty 09 – ZeMKI, Centre for Media, Communication and Information Research, University of Bremen
Funding period: 1 June 2023 – 30 November 2023