The Digital Revolution in the Social Sciences: Five Theses about Big Data and Other Recent Methodological Innovations from an Analytical Sociologist

In recent years, both scholars and policy-makers place big hopes in the emerging fields of data science and computational social science to solve not only academic puzzles, but also to cure many “real-world” problems in a wide range of areas such as health, crime, and poverty. In this paper, we re-evaluate these claims, highlight current problems of these nascent fields, and show what sociology has to contribute to and can gain from the digital revolution in the social sciences. We thereby focus on analytical sociology - a field at the intersection of classical sociology and modern computational social science, which places a strong emphasis on mechanism-based explanations and rigorous empirical analyses. In a nutshell, we argue that sociology has to bring a lot to the table with important contributions concerning not only substantive research questions, but also theoretical insights and methodological skills. Both sides - not only sociology, but also data science - could thus substantially profit from a closer exchange, while some problems still remain that hinder an even more fruitful collaboration.