ABSTRACT:

Can natural language processing (NLP) help us understand and address important social issues and problems? I first describe a series of studies conducted by our large multidisciplinary team at Stanford that use NLP/computational linguistics in combination with social psychology to automatically analyze traffic stop interactions between police officers and community members from police body-worn camera footage. We draw on linguistic models of dialogue structure and of interpersonal relations like respect to automatically quantify aspects of these interactions. I’ll describe the differences we find in the language directed toward black versus white community members, demonstrate the relationship with escalation, and discuss training for improving the relations between police officers and the communities they serve. Next, I’ll discuss our similarly multidisciplinary analysis of the language used by politicians to describe immigrants over a large part of our nation’s history, by examining 140 years of congressional speeches. We trace the time-course of polarization on the immigration issue, offer novel computational tools for detecting metaphorical language and measuring dehumanization, and demonstrate the remarkable similarity between the often toxic language used to describe Chinese immigrants in the 19th century and Mexican immigrants in the 21st. Together, these studies highlight how natural language processing can help us interpret latent social content behind the words we use.

BIO:

Dan Jurafsky is Professor of Computer Science, Professor of Linguistics, and Reynolds Professor in Humanities at Stanford University. He was a 2002 MacArthur Fellow and is a member of the American Academy of Arts and Sciences and a fellow of the Association for Computational Linguistics, the Linguistics Society of America, and the American Association for the Advancement of Science. He is the co-author of a standard textbook in NLP, and co-created the first massively open online course in NLP. His trade book “The Language of Food: A Linguist Reads the Menu” was a finalist for the James Beard Award. His research ranges widely across NLP as well as its applications to the behavioral and social sciences.

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