Computational social science is an interdisciplinary field that advances theories of human behaviour by applying computational techniques to large-scale data from social media, dynamic networks, real-time digitised and administrative records, and social simulations. The integration of social science with computer science and engineering fields provides novel tools to mine an unprecedented amount of complex data, coupled with analytic methods such as automated text analysis, online field experiments, machine learning, and computational modeling. This emerging field collectively addresses longstanding sociological questions—many of which have been difficult to be unearthed by traditional survey methods.

The major initiative of this research cluster is to leverage the cutting-edge tools of computational social science to push forward the substantive areas of our department’s existing and emerging strengths, including (1) China studies, (2) population health; (3) social networks and group dynamics; (4) crime and deviance. This cluster runs a tight-knit working group where professors and postgraduate students present research biweekly and occasionally hosts hands-on method workshops.