aau/MüllerThe SoWi Methods Hub at the Faculty of Social Sciences officially launched on 5 October 2026. The Hub is designed to foster exchange on research methods and practices across different disciplines. It aims to provide researchers and students with opportunities to explore methodological questions and develop their skills through summer schools, workshops, tutorials, and resources for innovative teaching in research methods. The core team comprises Rainer Alexandrowicz, Martina Blank, Valerie Hase, and Christof Lammer. Following welcoming remarks by Rector Ada Pellert and Dean Judith Glück, the core team discussed current challenges and future perspectives. The discussion was moderated by Larissa Krainer. 

What research methods are used in your departments?
Rainer Alexandrowicz: My own work is firmly rooted in quantitative methods – essentially, statistics. Looking beyond my particular area of expertise, however, psychology draws equally on quantitative and qualitative approaches. I am very glad that this is the case. When I began my studies, which also included sociology, back in the last millennium, there were still fierce disputes over research methods. It was dreadful! Some people pursued qualitative research because they did not understand the summation symbol, while others pursued quantitative research because they did not understand Max Weber. Fortunately, we’ve left those debates now behind. and learned that each method has its strengths and areas of application.
Martina Blank: As you know, geography is a discipline that encompasses an exceptionally broad range of approaches – from the natural sciences and critical rationalism to qualitative research grounded in social constructivism. Geography has perhaps always brought these different perspectives together within a single discipline, but we have also had our share of methodological disputes. Human geography has repeatedly shifted between quantitative and qualitative approaches. In the 1960s, progressive movements sought to replace traditional regional geography with ‘hard’ science. This was followed by another shift in the 1990s towards a more qualitative perspective. My ethnographic research lies at one end of this spectrum, but I also value geography’s strong tradition of fieldwork. We enjoy going into the field and observing things first-hand.
Valerie Hase: I can build on that from the perspective of computational methods in media and communication studies, which is my main area of expertise. Scholars using computational methods are often criticized for collecting data and simply applying a method to it, without much theoretical foundation. I am trying to challenge that misconception. I am a media and communication researcher and have also undertaken additional training in research methods, so my work is highly interdisciplinary. I make extensive use of automation, for example to investigate digital trace data: What information do major technology companies collect about you when you use your smartphone, when you are online – and even when you are offline? How can we access these data? My second area of focus is natural language processing (NLP), which is also used in computational linguistics. The central question here is how to analyse large text corpora. My aim is to make this research more firmly grounded in theory. I also collaborate with computer scientists and seek to integrate computational methods with qualitative research. For example, I am trying to collect and analyse automatically the million or so data points that Facebook holds about you, and then discuss those data with you in an interview. I might ask: What was happening in your life that year that made you spend so much or so little time online?
Christof Lammer: I would like to second the point about connecting methods with theory. When someone asks me which methods I use, my initial reaction is one of considerable discomfort. I feel that the question forces me to isolate certain aspects of my research practice and label them as methods, even though I do not think my work actually operates in that way. My research is primarily ethnographic. Ethnography encompasses a range of methods, which can also include quantitative surveys. At its heart, however, is participant observation. The method is entirely low-tech: all you need is a pen and a piece of paper. You simply enter a social situation and do what anyone encountering a new situation would do: listen, observe, talk, and participate. But that alone would not enable me to produce meaningful social scientific knowledge. If I engage in participant observation without the appropriate theoretical concepts, I cannot recognise what matters. I cannot identify the right situations to observe or ask the right questions. For me, theoretical concepts are therefore also methodological tools.
A conventional methods centre of the kind found at many universities, with specialist staff providing expertise in particular methods, would not be especially helpful for my research practice. I find our concept for the Hub extremely valuable because it focuses on exchange and coordination while recognising differences between research approaches. It makes expertise more visible without disembedding researchers and students from the theoretical and empirical contexts of their work.
How have research methods evolved within the different disciplines, and what are the implications for interdisciplinary collaboration?
Valerie Hase: Media and communication studies draws on a broad range of methods. For a long time, the discipline had a tradition closely aligned with the humanities, with a strong emphasis on qualitative approaches. In the 1960s, there was a shift towards empirical social science research, and we adopted and adapted many methods from sociology and psychology. Over the past ten to fifteen years, as in many other social science disciplines, we have experienced a computational turn, involving efforts to automate research methods. This presents both an opportunity and a challenge: we draw on many methods from other disciplines, but we need to adapt them to our own standards. We have also become considerably better at developing methods of our own. Content analysis and the analysis of digital trace data are examples of this.
Rainer Alexandrowicz: One major transformation in our field came with computational statistics. Eighty years ago, the term ‘computer’ still referred to people who sat together in rooms inverting matrices or calculating logarithms. Fortunately, machines have now taken over that work. Today, a factor analysis no longer takes an entire weekend but just microseconds. In the late 1990s and early 2000s, the increasing computing power available even in our homes made entirely new computational approaches possible. This was particularly evident in the rapid rise of Bayesian statistics. It sparked something of a revolution in our field, and now AI systems are bringing another major transformation. I see this as a profound paradigm shift the full significance of which might be assessed in ten or twenty years. I believe meta-analyses will develop considerably as processing large volumes of text becomes easier. Qualitative research is also benefiting: I no longer have to transcribe interviews myself. That alone makes an enormous difference. Data are available to me faster than ever before – but this also creates a strong temptation to let the computer analyse them straight away.
Martina Blank: Geography encompasses such an exceptionally broad range of approaches that even a colleague from my own department and I would probably struggle to agree on a few key developments. Let me approach the question differently. In qualitative research, which is where my work is situated, there has been a significant shift in how we think about relevance and about the people we work with in our research. David Harvey is apparently the world’s most widely read living geographer. During his time in Britain, he conducted quantitative spatial analyses, which represented a very abstract approach to geography. He then moved to the United States at a time when Baltimore was experiencing civil unrest. He began investigating what was happening there. The social questions he encountered led him to explore different methods. This does not mean that quantitative methods cannot be used effectively to investigate such questions. Quite the opposite: David Harvey always maintained that we need both approaches. Both are relevant. In this context, I would say that an applied yet critical approach, together with an awareness of wider social developments, is particularly important in our discipline. This has also led to a greater emphasis on participatory research, including in my own work. We increasingly regard the people we study as research partners, developing research questions and analysing findings together, and sometimes even co-authoring publications. This shift concerns one strand of geography rather than the discipline as a whole.
Christof Lammer: I could say a great deal about the history of research methods in social and cultural anthropology, the discipline in which I was trained. Today, however, I would like to examine that history from the perspective of science and technology studies, my field here at the University of Klagenfurt. One of the central insights of science and technology studies is that scientific practices are always social practices as well. Looking at social and cultural anthropology, we find that the separation between theory and method has not been institutionalised through specialised professorships. Nevertheless, there have been periods when methodological instructions played a very important role. In the early days, these instructions were extremely detailed. This was the era when so-called armchair anthropologists sat in the imperial metropoles and instructed colonial officials, travellers, and missionaries on how to collect data. This shows us that methods have a great deal to do with the social organisation of scientific work and less to do with fundamental epistemological questions. In fact, I think the relationship works the other way round: the way people work together determines whether and how methods become a subject of discussion. I first encountered this idea through the sociologist Stefan Hirschauer, who argues that quantitative survey research involves ‘empirical workers’, who conduct surveys and generate data for low wages, and ‘theoretical capitalists’, who then use those data to calculate correlations, produce publications, and reap the benefits. The example of armchair anthropologists shows that strict methodological instructions are not confined to quantitative research. They therefore cannot be explained solely by different epistemological approaches. Whether such methodological prescriptions exist depends largely on how scientific work is organised within the administrative and organisational structures of universities and society. From this perspective, the current concern with methods is best seen as a response to the shifting division of labour in scientific practice, with certain tasks being delegated to human and non-human actors, such as computers. As Rainer reminded us, computers used to be people; now they are machines. Whether the work is carried out by interviewers, colonial officials, or computers, it is always the division of labour that raises the questions: What are our methods? And what methodological directives do we need? Participatory research – involving the people being studied in the process of knowledge production – is no exception. Here, too, we need to negotiate who does what. Understanding scientific methods as social practices that entail social responsibilities is an approach we should continue to develop at the SoWi Methods Hub. It is a strength that distinguishes us from other methods centres.
Looking ahead, what are the main challenges facing the social sciences, given their diversity? How can the SoWi Methods Hub help address them?
Rainer Alexandrowicz: I see the rise of AI as the central challenge we face. We now have incredibly powerful tools that allow us to find and explore information quickly. In my own field, I can use AI as an ideal tutor. If I ask the system what a correlation is, I receive a fairly sensible answer. This allows me to familiarise myself with new topics very quickly. On the other hand, there are also more troubling possibilities, such as allowing a system to carry out an entire analysis based on sources that I can no longer trace let alone verify. The challenge, as I see it, is to integrate these tools in a meaningful way and manage the problem of AI hallucinations without being misled by serious errors. We need to avoid moving directly from the replication crisis into a hallucination crisis.
Valerie Hase: One thing I found fascinating when we were setting up the Hub was how often we used different terminology to describe the same thing. Sometimes it took three meetings over coffee before we realised that we were actually talking about the same problem. This happens because we approach issues from the perspective of our own disciplines and assume that things work differently elsewhere. Returning to the question of how algorithms affect us: computational methods depend on training data, which first have to be produced. This work is often carried out by very poorly paid workers in other countries. There is extensive discussion in critical data studies about the conditions these workers face and the implications for data quality. What I find particularly interesting is that similar issues have been debated in other disciplines for much longer.
Christof Lammer: I see the main challenges facing ethnographic practice, both in research and teaching, as arising from its social embeddedness, particularly from administrative requirements and targets. Ethnographic research needs time. It also involves periods when little appears to be happening, but it can provide unique insights precisely because it goes beyond existing data. Requirements to complete theses and dissertations within short timeframes make certain research practices impossible and, consequently, prevent particular research questions from being explored. Time constraints and standardised ethical requirements, which are often motivated by liability concerns and institutional risk management, can make research practices such as participant observation unworkable, because they depend on the gradual building of relationships and trust. By facilitating exchange and dialogue, the SoWi Methods Hub can highlight the needs of different research practices and foster a better understanding of what they require to thrive.
Martina Blank: A great deal comes down to understanding methods. I often find that I do not fully understand what my colleagues are doing. At the same time, particularly because we work in transdisciplinary contexts, we are very much concerned with rebuilding trust in science. It is important for us to continue learning how different methods work so that we can contribute meaningfully to debates in which science itself is being challenged. That is what I personally hope to gain most from the Hub: the opportunity to explore these different worlds and understand them.
 

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Visit the SoWi Methods Hub website
Der Beitrag Methods in dialogue: the SoWi Methods Hub gets under way erschien zuerst auf University of Klagenfurt.