Mixed methods

Robust methods are key to reliable research findings. As subject matter of research gets more complex and interdisciplinary, new methods are required. Methodological innovation is an inherent part of scientific renewal. In particular, I am interested in combination of various approaches.

Related publications

Digital Russia Studies: An Introduction (2021)

The global digitalization trend and the major societal shifts that accompany the process of converting ever more information and communications into digital form, challenge and transform existing practices across all spheres of life. In many ways, the digital transformation Russia is undergoing is far from unique. At the same time, the impact of and responses to these digitalization practices in Russia are evidently context driven. For researchers investigating Russia, digitalization has resulted in the emergence of a wealth of new (big) data sources, including social media and other kinds of digital-born content that allow us to investigate Russian society in novel ways. The Palgrave Handbook of Digital Russia Studies aims to contribute to and consolidate a methodological broadening in area studies. Digital Russia studies focuses on the digital transformation of the (geographical) area of study, while digital Russia Studies indicates the use of digital sources and methods in studying it and that is only partially captured by the term digital humanities. Together, Digital Russia Studies emphasizes how these two research lines are intertwined, interdependent, and mutually reinforcing.  

Topic modeling and text analysis for qualitative policy research (2019)

This paper contributes to a critical methodological discussion that has direct ramifications for policy studies: how computational methods can be concretely incorporated into existing processes of textual analysis and interpretation without compromising scientific integrity. We focus on the computational method of topic modeling and investigate how it interacts with two larger families of qualitative methods: content and classification methods characterized by interest in words as communication units and discourse and representation methods characterized by interest in the meaning of communicative acts. Based on analysis of recent academic publications that have used topic modeling for textual analysis, our findings show that different mixed‐method research designs are appropriate when combining topic modeling with the two groups of methods.