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It is often claimed that the rise of so called ‘big data’ and computationally advanced methods may exacerbate tensions between disciplines like data science and anthropology. This paper is an attempt to reflect on these possible tensions and their resolution, empirically. It contributes to a growing body of literature which observes interdisciplinary collabrations around new methods and digital infrastructures in practice but argues that many existing arrangements for interdisciplinary collaboration enforce a separation between disciplines in which identities are not really put at risk. In order to disrupt these standard roles and routines we put on a series of workshops in which mainly self-identified qualitative or non-technical researchers were encouraged to use digital tools (scrapers, automated text analysis and data visualisations). The paper focuses on three empirical examples from the workshops in which tensions, both between disciplines and methods, flared up and how they were ultimately managed or settled. In order to characterise both these tensions and negotiating strategies I draw on Woolgar and Stengers’ use of the humour and irony to describe how disciplines relate to each others truth claims. I conclude that while there is great potential in more open-ended collaborative settings, qualitative social scientists may need to confront some of their own disciplinary baggage in order for better dialogue and more radical mixings between disciplines to occur.

(open panel at EASST 2022)

The large-scale fraud of social psychologist Diederik Stapel has fuelled debates about the state of the discipline and the need for reform. Stapel became a tool to think with in the crisis in psychology. In the process a collection of imposters and truth-tellers were constructed and performed, each representing a different relation to the truth. Whereas Stapel was denounced as a cynical con man by his colleagues, he himself performed the role of a tragic imposter, and while many social psychologists presented themselves as the unwitting victims of Stapel, critics saw the affair as evidence that psychology is a wannabe science in need of fundamental reform. The various imposters and truth-tellers that made their appearance imply different ways of drawing distinctions between honesty and deception, appearance and reality, truth and story telling, frankness and civility.

Supplemental material, TCAT Modulation Sequencer BBC for Quali-quantitative methods beyond networks: Studying information diffusion on Twitter with the Modulation Sequencer by David Moats and Erik Borra in Big Data & Society

Although the rapid growth of digital data and computationally advanced methods in the social sciences has in many ways exacerbated tensions between the so-called ‘quantitative’ and ‘qualitative’ approaches, it has also been provocatively argued that the ubiquity of digital data, particularly online data, finally allows for the reconciliation of these two opposing research traditions. Indeed, a growing number of ‘qualitatively’ inclined researchers are beginning to use computational techniques in more critical, reflexive and hermeneutic ways. However, many of these claims for ‘quali-quantitative’ methods hinge on a single technique: the network graph. Networks are relational, allow for the questioning of rigid categories and zooming from individual cases to patterns at the aggregate. While not refuting the use of networks in these studies, this paper argues that there must be other ways of doing quali-quantitative methods. We first consider a phenomenon which falls between quantitative and qualitative traditions but remains elusive to network graphs: the spread of information on Twitter. Through a case study of debates about nuclear power on Twitter, we develop a novel data visualisation called the modulation sequencer which depicts the spread of URLs over time and retains many of the key features of networks identified above. Finally, we reflect on the role of such tools for the project of quali-quantitative methods.

Supplemental material, TCAT Modulation Sequencer Treehugger for Quali-quantitative methods beyond networks: Studying information diffusion on Twitter with the Modulation Sequencer by David Moats and Erik Borra in Big Data & Society

Supplemental material, TCAT Modulation Sequencer RT for Quali-quantitative methods beyond networks: Studying information diffusion on Twitter with the Modulation Sequencer by David Moats and Erik Borra in Big Data & Society

This thesis considers the role of online platforms (Wikipedia, Facebook, Twitter, etc.) in digital social\ud research from a Science and Technology Studies (STS) perspective and proposes new conceptual,\ud methodological and visual tactics, drawing on a series of empirical case studies concerning controversies\ud over nuclear power.\ud \ud Recent work in STS seeks to map science controversies (GM foods, nanotechnology, climate change, etc.\ud Venturini 2010) using digital tools, which repurpose online platforms for social research (Rogers 2009).\ud Yet these platforms not only provide data about controversies, they may also intervene in them as well\ud andI propose that this requires studying them ‘in action’, drawing on the techniques of controversy\ud analysis (Latour 1987) and actor-network theory (ANT). However, this research presents several\ud challenges. How to delineate a study when controversies transcend particular platforms? How to define\ud what is relevant when these platforms have their own relevance-defining metrics? How to track\ud information flows within or between platforms?\ud \ud The central argument of this thesis is that while researchers should capitalise on the affordances of\ud these platforms, they must diverge from them as well. Theoretically, this means maintaining a tension\ud between studying controversies and studying the platforms themselves. Methodologically this means\ud decoupling methods from platform data structures: scraping less obvious data, juxtaposing quantitative\ud and qualitative traces and presenting data in novel ways. Over three case studies, I will develop a series\ud of mapping techniques for analysing controversies which qualify the quantitative and make the less\ud calculable more calculable, revealing imbalances in the articulation and dissemination of controversies\ud online which would remain hidden to platform-specific or qualitative approaches on their own. These\ud exploratory techniques, which draw on work in the sociology of scientific representations (Woolgar and\ud Lynch 1992), have implications for debates about big data, digital sociology, media studies and the\ud relationship between quantitative and qualitative methods.