Computational Social Science
New forms of data and advanced statistical techniques provide enormous research opportunities, yet the social sciences fall short of taking full advantage of them. A major obstacle is the lack of analytical approaches that are appropriate to both the questions and the data pertinent to the social sciences. This especially concerns the analysis of meaning in text—understood as shared reference structures that are reflected at the semantic, linguistic, and narrative level. This research group will develop methodological solutions to two core challenges in the analysis of text for the social sciences: (1) analyzing how conceptual meaning changes within time-stamped documents and (2) capturing distinct forms of meaning in interviews. Empirical applications of these solutions will explore important questions of history, politics, and culture and provide methodological guidance for the use of computational techniques and new forms of data more generally. Moreover, this group will advance research projects to better understand how different forms of meaning affect people's consumption of information online. Beyond immediate results, this project will lay the foundation and open new opportunities for leveraging modern forms of data and tools for answering questions in the social sciences.