The Social Production and Use of Video in Empirical Social Research

• Applicant: Professorin Dr. Ulrike T. Kissmann
• Subject Area: Empirical Social Research
• Term: since 2026
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 583692659

The technical development of social media, video surveillance cameras, and body cameras on the one hand, and the relevance of artificial intelligence on the other, are currently increasing the diversity and availability of video data, and this trend is set to continue in the future. Despite individual reflections on the empirical use of video data as research data from a Sociology of Scientific Knowledge perspective, there has been no targeted methodological comparison that critically examines the existing schism between qualitative and quantitative approaches. The planned scientific network will engage in dialogue with mixed and multimethod researchers to examine and compare the methodological and epistemological assumptions that lead to the production and use of video. Through joint exchange, the network will reflect on the claims to truth and validity as well as the quality criteria that are relevant for the collection, further processing, and analysis of the data. On the one hand, the network is based on the MMMR approach, i.e., Mixed Methods and Multi-Method Social Research. This is based on a broad understanding of method integration, which also includes the linking of methods within qualitative or quantitative approaches. On the other hand, the network draws upon perspectives from Science and Technology Studies and considers the production and use of video not in terms of a concept of science as science-as-made, but rather in terms of science-in-the-making, as first proposed in the laboratory studies of Bruno Latour and Steve Woolgar. The classification into quantitative versus qualitative is critically questioned in so far as the planned project asks how quantitative and qualitative data are generated and which methodological criteria are applied for this purpose. Finally, these perspectives are complemented by Critical Data Studies, because much video data is currently available as Big Video Data. The proposed network will explore in joint dialogue whether and to what extent (audio)visual data not only represent phenomena, but instead transform knowledge and thereby produce something new. This also includes the question of what constitutes the handling of research data from natural situations (in Garfinkel's sense) and how this may be changed by deepfakes of video data. To achieve these goals, first, an annual workshop with invited national and international speakers will be held, followed by an international conference for mixed and multimethod researchers working in the field of video. Second, joint research projects will be initiated be-tween network members, focusing either on meta-reflection or the application of integrated approaches with video. Third, the results of the network will contribute to optimizing the storage and reuse possibilities for video in existing repositories.

• DFG Programme: Scientific Networks