Science and technology studies is famous for questioning conceptual and material boundaries by following controversies that cut across them. However, it has recently been argued that in research involving online platforms, there are also more practical boundaries to negotiate that are created by the variable availability, visibility, and structuring of data. In this paper, I highlight a potential tension between our inclination toward following controversies and “following the medium” and suggest that sometimes following controversies might involve going “against platforms” as (...) well as with them. I will illustrate this dilemma through an analysis of the controversy over the coverage of the Fukushima disaster on English language Wikipedia, which concerns boundaries between expert and lay knowledge but also the social and technical functioning of Wikipedia itself. For this reason, I show that following the controversy might mean making use of less formatted and less obvious data than Wikipedia normally provides. While this is not an argument against the use of automated digital research tools such as scrapers, I suggest that both quantitative and qualitative researchers need to be more willing to tweak their approaches based on the specificities of the case. (shrink)

In this contribution to the colloquium, I argue why and how I lost interest in the overall structure of social networks even though Big Data techniques are increasingly simplifying the collection, organisation, and analysis of ever larger networks. The challenge that Big Data techniques pose to the social scientist, I think, is of a different nature. Big Data on social actors mainly record events, e.g. interactions between human beings that happen at a point in time. In contrast, social network analysts (...) tend to think in terms of social relations that exist over a timespan. The challenge, then, is to rethink our conceptions and models of social relations and social structure. I conceptualize social structure and social relations as forces. I propose modelling these forces with regression models for longitudinal interaction data. (shrink)