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- Convenors:
-
Ronja Trischler
(Technische Universität Dortmund)
Johannes Paßmann (Ruhr University Bochum)
Lisa Gerzen (Ruhr University Bochum)
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- Format:
- Traditional Open Panel
Short Abstract:
The panel aims to revive the methodological dialogue between STS and Digital Methods by asking what a consistent understanding of Digital Methods as a qualitative methodology might look like.
Long Abstract:
This panel aims to advance the dialogue between Science and Technology Studies and Digital Methods about their shared claims to qualitative methodologies. This dialogue has been ongoing since the early years of DM, as they were partly developed within, or at least with reference to, STS. Over time, however, significant parts of DM have evolved their own research logics. In order to harness the richness of digital data, they have proposed and developed novel ways of integrating non-human actors, in particular a wide range of tools and digital sources, into research procedures and point to the extensive ways in which digital data challenge traditional understandings of situated action – and thus of how to research it. However, the provision of large amounts of data and the development of digital tools to analyse them have often paid less attention to the qualitative origins and potentials of DM: digital tools often focus on the processes and operations of conducting digital media research, rather than explicitly discussing the methodological implications and potentials of these procedures. In particular, core questions of STS – such as the performativity of methods and research tools, and their implications for power relations in academic knowledge production – also have often remained unanswered. The panel will discuss how the methodological dialogue between DM and STS can be revived and how this can contribute to the advancement of both. In the panel discussions, we aim to draw on STS traditions to challenge and promote qualitative methods and methodologies with regard to their performativity in research practice and the diverse and messy participation of new technologies and media in this process. One of the most pressing questions we are considering is what a consistent understanding of DM as a qualitative methodology might look like.
Accepted papers:
Session 1Fiona Kinniburgh (Technical University of Munich) Nils Matzner (Technical University Munich) Silke Beck (TUM) Scott Frickel (Brown University) David Demortain (INRAE)
Short abstract:
This paper maps the current use of computational methods in STS, revealing limited adoption thus far. It suggests developing assemblages of methods where the productive effects of the combination of methods and data are reflexively discussed, developed, and put to work in research projects.
Long abstract:
There have now been multiple calls and propositions in social sciences writ large to connect the quantitative and qualitative, the computational and the ethnographic –– some specific to STS, others larger (Evans and Foster, 2019). Based on a bibliometric analysis of extant STS research, this paper maps the current use of computational methods in the field, revealing that only a limited set of computational possibilities have been embraced thus far. Given STS’s attentiveness to data in fields beyond itself, it is surprising that STS remains relatively disconnected from current developments in the computational field. Rather, these methods appear most prominently in journals catering to primary audiences beyond academic STS, extending into policy and communication domains.
Based on the prospects indicated in these papers and in ongoing discussions in our international research group meetings on computational methods in STS, we review potential avenues for computational methods to augment traditional methods used in STS. This paper suggests developing assemblages of methods where the productive effects of the combination of methods and data are reflexively discussed, developed, and put to work in research projects. We identify such possible productive effects and propose that such an approach allows for a more nuanced engagement with data and theory, facilitating a more responsive and impactful STS research agenda that can extend beyond academic boundaries as part of an engaged STS program.
Lina Franken (University of Vechta)
Short abstract:
Re-using research data is promising regarding filtering and comparison in combining computational and qualitative methods. The agency the data itself invoke is relevant here. Combining the perspectives to extended mixed methods approaches needs to be reflected regarding epistemological changes.
Long abstract:
Digital Methods are connected to STS and to the growing interdisciplinary field of Digital Humanities. There, the focus lies on quantitative approaches to closed corpora, often retro-digitized historical source material used for computational approaches. Qualitative perspectives are seldomly taken into account. Nevertheless, especially the re-use of available research data is promising, since one can find a huge rage of e.g. qualitative interview transcripts in repositories that make new comparative perspectives possible. Digital methods are promising in two directions: (1) filtering for relevant data and (2) comparing different datasets and thereby facilitate the use of larger corpora in qualitative settings.
No matter how well-elaborated computational methods are, qualitative research will always change the focus to a rather in-depths analysis of smaller parts of the corpus. The different agencies the data themselves invoke, when not being gathered in the field by researchers interpreting them, form an additional layer of how the digital processing of data influences researchers and their questions asked. Statements based on this are therefore constructed and limited in specific dimensions.
A major chance lies in combining approaches within the analysis. Methods can inform each other and through combining computational approaches with qualitative inquiry, the research question can be answered with a deeper understanding and on a broad basis of data, developing new and extended mixed methods approaches. Epistemological changes need to be taken into account.
The talk will argue for a development of digital methods for the re-use of qualitative interview transcripts, based on ongoing research and its reflection.
Lena Teigeler (University of Siegen) Carolin Gerlitz (University of Amsterdam)
Short abstract:
The presentation proposes interventions inspired by data feminism as qualitative dimensions of digital methods, by linking them to strands of methodological reflection made in STS, using the case of lists in platform research.
Long abstract:
Taking listmaking as a starting point, the presentation explores the reflexive, inventive and critical potential of digital research methodologies by drawing attention to the qualitative decision making and interpretative dimension involved. Lists are essential elements of social media platforms: Lists of popular topics, accounts, followers, likes, clicks, views, search results or feeds, provide orientation, structure our attention and guide practices of content reception and production. Content, they suggest, is particularly relevant when it is noticed by many, shared by many, commented by many. At the same time, researchers employ platform data and create lists themselves to approach issues, users or platform dynamics. The platforms’ logic of the many has inscribed itself in empirical platform research. Thereby, perspectives that move beyond the top users, the most used hashtags, the most shared URLs or the most active accounts are increasingly receding into the background. Inspired by discussions in data feminism (D'Ignazio and Klein 2020), we develop an alternative approach to Twitter/X data that questions how the platform aggregates diverse user activity into extrapolations of the many, by focusing on data that is not prominently displayed by the platform itself or even made invisible. Doing so, we link the propositions made by data feminism to different strands of methodological reflection proposed in the context of STS, such as attentiveness to inscriptions, interface methods, interpretative flexibility or situated research and explicate them as qualitative dimensions of digital methods research.
Miira Hill (University of Bremen) Cornelius Puschmann Patrick Zerrer (ZeMKI, Centre for Media, Communication and Information Research)
Short abstract:
This paper proposes a qualitative methodology for the analysis of digital tracking data. By exploring the qualitative dimensions of digital tracking, this paper contributes to advancing methodologies for studying evolving media consumption behaviors in the digital age.
Long abstract:
This paper introduces an innovative qualitative approach to tackle the challenges of digitization through a study of consumption habits in the media sector. Traditional methods, based on quantitative surveys and qualitative techniques such as observation and interviews, find themselves challenged in the evolving digital landscape. The swift movement of users within a digital environment with abundant choices, coupled with issues of survey recall and the intricacies of online intermediary structures, complicates the assessment of usage patterns (Grigoropoulou and Small 2022; Parry et al 2021; Thorson and Wells 2016).
The emergence of digital tracking offers a new avenue for investigation (Stier et al 2020). Participants use apps or browser plug-ins, enabling researchers to explore connections between information access, political preferences, and sociodemographic characteristics (Jürgens and Stark 2022; Merten et al 2022; Scharkow et al 2020). However, analyzing tracking data in the social science context poses significant challenges due to the enormous volume of data.
This paper proposes a qualitative methodology for the analysis of extensive tracking data, inspired by sequence analysis (Abbott 1995; Borgna and Struffolino 2018). With a representative sample of German internet users, the paper aims to uncover various patterns of incidental and habitual information acquisition by linking usage paths on mobile phones and desktop computers with collected online news content and attitudes expressed in an open survey item on the Russian invasion of Ukraine. The paper critically discusses the limitations of this technique and suggests approaches for a more robust mixed-methods analysis of extensive digital trace data.