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Professor of Analytical Sociology
About
I am Professor of Analytical Sociology and Director of the Excellence Center for Analytical Sociology at Linköping University.
My academic interests center on the dynamic interplay between micro behavior and macro outcomes, and the role that social interactions and social networks play in such processes. The philosophy and methodology of the social sciences is another core area of interest, and I have been one of the driving forces behind the development of analytical sociology.
During the last decade, much of my empirical research has focused on the role of social interactions in explaining various types of segregation processes. This research has been funded by grants from the European Research Council, the Swedish Research Council, and Riksbankens Jubileumsfond.
I received my PhD in Sociology at Harvard University. Before joining Linköping University, I have held professorial positions at the University of Chicago, Stockholm University, University of Oxford, Singapore Management University, and NYU Abu Dhabi.
Over the years I have had various leadership roles such as Director of the Institute for Analytical Sociology, Director of the Institute for Futures Studies in Stockholm, Dean of the School of Social Sciences at Singapore Management University, President of the International Network of Analytical Sociology, Chair of the Sociology Department at Stockholm University, and Chair of the Sociology Group at Nuffield College.
I am a fellow of the Royal Swedish Academy of Sciences, the Royal Swedish Academy of Letters, History and Antiquities, the Norwegian Academy of Science and Letters, Academia Europaea, and the European Academy of Sociology.
Current theoretical and empirical work
More than twenty-five years have now passed since the Royal Swedish Academy of Sciences conference on social mechanisms—an event that many regard as marking the emergence of analytical sociology in its contemporary form (see Hedström and Swedberg, Social Mechanisms: An Analytical Approach to Social Theory). Since then, the social sciences have developed substantially at the methodological, theoretical, and empirical levels. We now have access to analytical tools that enable a more precise understanding of how large-scale social outcomes are produced, as well as new forms of data and data-analytic techniques that allow theoretical and empirical work to be tightly integrated. Taken together, these developments make it possible to analyze and explain large-scale social processes with a level of precision and empirical fidelity that was unimaginable for earlier generations of social scientists.
I am currently working on a theoretically oriented monograph that builds on and reflects these developments. The preliminary title of the book is Reconstructing the Social: Relational Microstructures and Mechanisms in Analytical Sociology. It will be published by Cambridge University Press in late 2026 or early 2027.
Empirical research in the analytical-sociology tradition - A brief background
Empirical research in the analytical-sociology tradition seeks to explain collective outcomes by reference to the actions and interactions of the individuals who bring them about. Many outcomes of central sociological interest—such as school segregation, economic inequality, and the emergence of social and cultural norms—are the result of large numbers of individuals acting and interacting over extended periods of time.
Much empirical sociological research, however, has had a very different focus. It has either examined small groups of individuals in great detail or, when studying large populations, relied primarily on survey data. While survey data are well suited for many descriptive purposes, their random sampling design—where one individual is sampled in City X, another in City Y, and so on—is problematic from a sociological perspective because it precludes the analysis of social interactions and other forms of social interdependencies.
As a consequence, a persistent gap has existed throughout the history of sociology between the concerns of sociological theory and the practices of empirical research. This gap has been deeply unfortunate for the discipline, as it has limited the extent to which empirical research can directly inform the development and refinement of sociological theory.
Against this background, the present moment is an exceptionally promising one for sociology. For the first time in the discipline’s history, data are becoming available on large populations of interacting individuals, enabling empirical analyses of the dynamic processes that link micro-level behavior to macro-level outcomes. The data in question include various forms of digital trace data as well as national population registers of the kind available in countries such as Denmark, Sweden, Norway, and the Netherlands. In parallel with these advances in data availability, there has been rapid progress in computational methods for analyzing large-scale, interaction-rich data.
The articles below illustrate how these developments make it possible to tightly link micro- and macro-level dynamics. They examine three distinct collective outcomes—music popularity, ethnic school segregation, and gender inequality in the labor market—but share a common explanatory strategy. In each case, the analysis centers on clearly specified mechanisms and draws on data from large populations of interacting individuals who, over time, generate the collective outcomes to be explained. All three articles employ large-scale agent-based simulations, carefully calibrated to the empirical data, to estimate the causal effects of well-defined micro-level interventions on emergent macro-level outcomes. Such an approach is of fundamental importance for empirical research in the analytical-sociology tradition.
Arvidsson, M., Hedström, P. & Keuschnigg, M. (2025). Wide social influence and the emergence of the unexpected: An empirical test using Spotify data. Sociological Science.
Social-influence processes not only affect the rate at which behaviors spread but can also decouple adoption behavior from individual preferences, and thereby bring about unexpected collective outcomes that cannot be predicted on the basis of the initial likes and dislikes of the individuals involved. However, the conditions under which social influence can lead to such decoupling are not well understood. We identify a social-influence mechanism that widens individuals’ behavioral repertoires and breaks the link between individuals’ initial preferences and the collective outcomes they jointly bring about. We test the micro-level assumptions of the mechanism in the context of cultural choices on Spotify, combining topic modeling with traditional statistical matching to estimate peer-to-peer influence effects from digital trace data. We then use agent-based simulations to examine the macro-level consequences of “wide” social influence and its importance for explaining cultural change.
https://sociologicalscience.com/download/vol_12/october/SocSci_v12_715to742.pdf
Mutgan, S., Hedström, P. & Arvidsson, M. (2025). "Ethnic preferences, opportunity structure, and the school segregation process". European Sociological Review.
Previous research has shown that parents often have strong ethnicity-related school preferences, and it has been suggested that these preferences are consequential for the ethnic segregation of schools. In this article, we study all students enrolled in compulsory schooling in the Stockholm region during the years 2008 to 2017. Using a combination of statistical analyses of school choices and large-scale, empirically calibrated simulations, we investigate how preferences and opportunities jointly influence the students’ mobility between schools and the school segregation that their mobility or lack thereof gave rise to. Our main finding is that opportunities generally outweigh preferences. While ethnicity-related school preferences exist, they have little impact on ethnic segregation because the schools that students move between tend to have similar ethnic compositions.
Arvidsson, M., Collet, F,. & Hedström, P. (2021). "The Trojan-horse mechanism: How networks reduce gender segregation." Science Advances, 7(16).
The segregation of labor markets along ethnic and gender lines is socially highly consequential, and the social science literature has long viewed homophily and network-based job recruitments as some of its most crucial drivers. Here, we focus on a previously unidentified mechanism, the Trojan-horse mechanism, which, in contradiction to the main tenet of previous research, suggests that network-based recruitment reduce rather than increase segregation levels. We identify the conditions under which networks are desegregating, and using unique data on all individuals and all workplaces located in the Stockholm region during the years 2000–2017, we find strong empirical evidence for the Trojan-horse mechanism and its role in the gender segregation of labor markets.
Contact information:
Linköping University
Institute for Analytical Sociology
601 74 Norrköping
SWEDEN
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