Project duration: 2025–2027. Research project funded by the German Research Foundation (DFG).
Researchers of the digital communication of non-institutionalized actors are confronted with several challenges concerning (1) the systematic definition, sampling, and identification of relevant actors, and (2) the specific classification of relevant actors and their content based on ideological, typological, and other content-based characteristics. The project aims to contribute to an increased reliability and validity in the identification and classification of heterogeneous actor groups on digital platforms. Its design comprises various identification, classification, and simulation studies based on manual and computational analyses. Different methods of identification and classification of radical and extremist actors on Telegram are assessed with regard to their reliability and validity (RQ1). Further, it is studied how researchers' decisions in the identification or classification stage of research might influence the identified actor groups and research outcomes on Telegram in subsequent steps (RQ2).
To this end, a) different strategies for the identification, sampling, and classification of the digital communication of radical and extreme actors are systematized. After, b), identifying the (approximate) entirety of this target population via network-based sampling, the actors will be, c), classified using manual and computational methods with varying specifications to collect their characteristics. Further, d) different possible researcher decisions during the identification and classification stage will be simulated to evaluate their consequences on later research outcomes. E) Documentation and archiving of a reference dataset will ensure the long-term accessibility and reusability of the project’s results, which will also be communicated to civil society actors and academic stakeholders via best-practice publications.
