A new kind of scientific endeavor -- computational social science -- is emerging at the intersection of social science and computer science. The field draws from a rich base of existing theory from psychology, sociology, economics, and other social sciences, as well as from the formal languages and algorithms of computer science. The result is an unprecedented opportunity to revolutionize the social sciences, expand the reach and impact of computer science, and enable decision-makers to understand the complex systems and social interactions that we must manage in order to address fundamental challenges of economic welfare, energy production, sustainability, health care, education, and crime.
In this talk, I will describe a project underway in my research group to develop and apply new formal languages and algorithms for discovering cause-and-effect dependencies in large social science data sets. I will use an extended historical example demonstrating the opportunities and challenges presented by the complex data sets generated by social systems. I will also describe several modern applications such as detecting stock fraud and understanding the incentive structures in online communities.
Bio: David Jensen is Associate Professor of Computer Science and Director of the Knowledge Discovery Laboratory at the University of Massachusetts Amherst. His current research focuses on machine learning, computational social science, social network analysis, and privacy. He received the 2011 Outstanding Teacher Award from the University of Massachusetts College of Natural Science. From 1991 to 1995, he served as an analyst with the Office of Technology Assessment, an agency of the United States Congress. He received his doctorate from Washington University in St. Louis in 1992.