Detecting Socialbots with the Help of Qualitative Research Methods?

Dr Florian Muhle (Bielefeld University, Faculty of Sociology)

In these days we are witnessing the arrival of new socio-technical entities: socialbots, which are automated software programs that control accounts on Online Social Networks in order to perform activities like posting messages and sending connection requests to other users, while presenting themselves as human beings (see Boshmaf et al. 2011). Especially in the context of the last U.S. Presidential election in 2016 these socio-technical entities gained questionable fame, because they were considered as infiltrating political discourse, distorting online discussions and manipulating public opinion. 

Against this background it is not surprising that (computer) scientists put a lot of effort in developing methods for socialbot detection. Not surprisingly (but somehow ironically), these methods are computer-based and therefore automated as well. But must methods for bot detection necessarily be automated as well? Or are there other options to deal with the task to spot socialbots. These questions are guiding the presentation, which presents initial methodological considerations from the research project ‘Socialbots as political actors?, which is a research cooperation between ANU and Bielefeld University (Germany), funded by the German Academic Exchange Service (DAAD).

Starting with a description of existing methods for bot detection, an alternative approach will be presented which combines computational sociology with qualitative research methods and social theoretical reasoning in an innovative way.