Analytical sociology and computational social science

Abstract

Analytical sociology focuses on social interactions among individuals and the hard-to-predict aggregate outcomes they bring about. It seeks to identify generalizable mechanisms giving rise to emergent properties of social systems which, in turn, feed back on individual decision-making. This research program benefits from computational tools such as agent-based simulations, machine learning, and large-scale web experiments, and has considerable overlap with the nascent field of computational social science. By providing relevant analytical tools to rigorously address sociology's core questions, computational social science has the potential to advance sociology in a similar way that the introduction of econometrics advanced economics during the last half century. Computational social scientists from computer science and physics often see as their main task to establish empirical regularities which they view as ''social laws.'' From the perspective of the social sciences, references to social laws appear unfounded and misplaced, however, and in this article we outline how analytical sociology, with its theory-grounded approach to computational social science, can help to move the field forward from mere descriptions and predictions to the explanation of social phenomena.

Complex Contagions and the Diffusion of Innovations: Evidence from a Small-N Study

“…Kalter and Kroneberg 2014; Léon-Medina 2017), and demonstrates that this perspective is not only compatible with big-data approaches (for a recent statement, see Keuschnigg et al 2017) but can equally well guide qualitatively-oriented, small-N studies. Finally, our paper shows that ethnoarcheology, when coupled with refined quantitative methods, and simulation techniques, is indeed able to identify robust generative causal patterns that can serve as explanatory building blocks for comparable contexts for which all required empirical information may not be available (for a recent debate, see Gosselain 2016; Roux 2017).…”

Computational Conflict Research

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Reformulating computational social science with citizen social science: the case of a community-based mental health care research

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