The Institute for Social and Economic Research and Policy (ISERP) and the Data Science Institute are jointly organizing a two-week workshop on data science for social scientists
- When: May 21st - June 1st, 2018
- Where: IAB 270B
- Daily schedule: 9am to 4pm (9am to 1pm consists of a lecture + lunch talk and 1pm to 4pm is a lab session)
- Who should apply: Faculty and researchers in the social sciences and SIPA interested in learning more about science.
While many social scientists use quantitative data, the increasing volume of digitized and “born digital” collections of books, articles, documents, and social media present tremendous new opportunities for research. But for those with little training in computer science, the barriers to entry can seem daunting.
Columbia’s Working Group on Computational Social Science is therefore offering a new workshop to offer a very practical introduction to computer packages accessible to researchers with varying skill sets. Participants will learn how to organize and analyze textual data, get an overview of advances in natural language processing and machine learning, see how they can grapple with old research problems with new rigor, and take on entirely new kinds of questions.
Click here to START (detailed course information and setup instructions.)
Raymond Hicks (@arpie71) is project manager at History Lab at Columbia University. Before coming to Columbia, he was statistical programmer for the Niehaus Center for Globalization and Governance at Princeton University. His research interests include the politics of trade and monetary policy as well as methodology. His work has appeared in The Journal of Politics, the British Journal of Political Science, International Organization, and International Studies Quarterly, among other journals. His current projects use textual data to explore questions about trade policy.