"Does This Vehicle Belong to You?": Computational Extraction of Social Meaning from Language
Dan Jurafsky, Stanford University
Police body-worn cameras have the potential to play an important role in understanding and improving police-community relations. In this talk I describe a series of studies conducted by our large interdisciplinary team at Stanford that use speech and natural language processing on body-camera recordings to model the interactions between police officers and community members in traffic stops. We draw on linguistic models of dialogue structure and of interpersonal relations like respect to automatically quantify aspects of the interaction from the text and audio. I describe the differences we find in the language directed toward black versus white community members, and offer suggestions for how these findings can be used to help improve the relations between police officers and the communities they serve. I'll also cover a number of our results on using computational methods to uncover historical societal biases, and detect framing, agenda-setting and political polarization in the media. Together, these studies highlight how natural language processing can help us interpret latent social content behind the words we use.
Bio: Dan Jurafsky is the Jackson Eli Reynolds Professor in Humanities, Professor of Computer Science, and Professor and Chair of Linguistics at Stanford University. He studies natural language processing, especially the extraction of meaning, intention, and affect from text and conversation, and applications to the social and cognitive sciences. Dan is the co-author of the widely-used textbook "Speech and Language Processing" and co-taught the first massive open online class on natural language processing. The recipient of a 2002 MacArthur Fellowship, Dan is also a James Beard Award Nominee for his book, "The Language of Food: A Linguist Reads the Menu".