Keynote: Machine Learning for Social Science SciPy 2016 Hanna Wallach

In this talk, I will introduce the audience to the emerging area of computational social science, focusing on how machine learning for social science differs from machine learning in other contexts. I will present two related models -- both based on Bayesian Poisson tensor decomposition -- for uncovering latent structure from count data. The first is for uncovering topics in previously classified government documents, while the second is for uncovering multilateral relations from country-to-country interaction data. Finally, I will talk briefly about the broader ethical implications of analyzing social data. Hanna Wallach is a Senior Researcher at Microsoft Research New York City and an Adjunct Associate Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst.