Kursinformation

This course highlights the ways in which sociologists are using tools from computational social science (CSS) to further social research. Digital trace data, large-scale online experiments, agent-based modeling, and computational text analysis, enable sociologists to analyze how large-scale properties of social systems emerge from human interaction. We will develop a perspective on how CSS techniques can be successfully deployed in social research, particularly when testing theories of socially influenced behavior prone to complex social dynamics and hard-to-predict collective outcomes. These tools, when applied using a theory-grounded approach, offer sociologists a chance to transcend the limitations of the dominant survey-research paradigm and address “big” sociological questions.

We will discuss various CSS techniques including analysis of big internet data, computer simulation, social network analysis, computational text analysis, and experimental methods. The focus of the course is to understand how these methods can provide new insights and push the boundaries of sociological inquiry. Important phenomena (or “social problems”) of our time serve as use cases in the course sessions. These include the acceleration of collective attention; political polarization; the diffusion of fashions, rumors, and misinformation; collective meaning making; algorithmic biases; discrimination; social exclusion online and offline. The course will also forge closer links between “qualitative” and “quantitative” research traditions, and we will discuss the methodological and ethical challenges that come with using the CSS toolbox. The overall objective is to encourage students to consider non-traditional analysis approaches in their own work.