"This programme is responding to the world."

Meet the Programme Director of Social Scientific Data Analysis

About Chris

Christopher S. Swader is a comparative sociologist with previous academic appointments at the Higher School of Economics in Moscow and the University of Bremen in Germany. He earned his PhD in Sociology with the Graduate School of Social Sciences in Bremen. Focusing on the connection between intimacy and normative order, he publishes on themes close to family sociology and the sociology of intimacy, economic sociology, anomie, post-socialism, and the life course.  His current main research endeavour is a multi-method investigation of loneliness in cities, which includes the ’Corona Diaries’ project, a gathering of narrative accounts about people’s experiences of COVID-19-related social distancing. For 5 years, he worked as Graduate School’s Methods Director (Social Sciences Faculty at LU), and he has very diverse methodological interests, including the philosophy of science, quantitative and computational approaches, and qualitative and ethnographic methods. Chris also has interdisciplinary experiences and has degrees or extensive experience in Russian Language and Area Studies, Global Studies, and International Relations. 

Our interview with Chris

What is the most enjoyable part about teaching?

Most enjoyable for me is when people find a passion in something, ideally in something new. I think that many of us are here for this process of discovery and the excitement that it kindles. So the most enjoyable is when students (and I) are all learning something new and motivated by that process. I guess I might split this idea into three parts: motivation, critique, and a desire to try something new (and something difficult).

Motivation really comes from within, but at the same time, we are inspired when we see others who are also motivated. It can be contagious to see that others also have a passion for something difficult. I think that what is happening in those moments is that we see that someone else’s motives might be similar to ours: not merely some kind of outcome on paper but also the process of learning something.

Critique, particularly self-critique, is linked to this process of discovery for me. Learning only truly happens when we challenge, rebuild, or append what we previously thought we know. So it is important to have a healthy amount of self-critique in order to be able to learn something new. Of course, critiquing ’established’ thoughts that are not our own can be just as enjoyable. For me, this is a core part of learning and discovery, and seeing students exercise this power is very inspiring.

Finally, I think these points all come together when students (and I) are dealing with challenging subjects. The themes and the skills that are the most complex are therefore the most enjoyable to master.

What's unique about this programme?

This programme is responding to the world. Our societies become more digitalized, and this is also happening to the worlds of commerce, science, and governance. Data and new means of analysing it are evolving more rapidly than ever before, and most organizations need staff members with expertise in data, analysis, as well as the social dimensions they are tasked with. This programme is really about thinking about modern and diverse data analysis techniques and being able to apply them to pressing problems, for example related to democratization, social and economic inequalities, and other pressing real-world problems.  It also creates a local ‘home’ for those interested in applying diverse data analysis techniques to social-scientific questions.

What will students learn?

This programme warmly welcomes students with diverse backgrounds and interests. We will support our students in learning to analyse various types of data in interesting and theoretically relevant ways in order to address socially important topics. They should leave with a strong skill set in qualitative and quantitative methods, in research design and methodology, in working with the R programming language, in theory-building, and in communicating their analyses to other scientists and to other stakeholders.

What kind of career is possible after pursuing this programme?

Data-literacy, methods and analysis skills, and the ability to apply these to diverse real-world problems are a powerful skill set, which is increasingly in demand in our increasingly data-driven world. Graduates of the Social Scientific Data Analysis programme should be well suited to contribute to a variety of professional social data analysis environments, for example as social data analysts, professional researchers, and research managers within state or non-governmental organizations, as well as in the private sphere (for example, in relation to market research, labour market research, or intelligence analysis). Graduates will also be well-suited, because of our training in methodology, theory, and publication, to pursue a PhD in the social sciences.