Fellow with the Institute for Policy Research

Northwestern University

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Computational linguist Rob Voigt develops natural language processing and machine learning methods to better understand the linguistic mechanisms of the social world. At the heart of his research program lies the simple but powerful insight that large-scale social structures—both the recognizable structures of institutions, organizations, and social groups, but also more diffuse structures such as social biases, polarization, and intergroup conflict—are ultimately the aggregation of many person-to-person interactions, often primarily conducted in the medium of language. Linguistics provides a theoretical toolkit to unpack the behaviors that make up these interactions, and computational methods offer a framework for scaling up to understand the effects of context and social factors like race and gender.

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His work addresses a broad range of questions related to bias and social conflict, including racial disparities in police language, media depictions of social groups, and the role of body language, gesture, and the voice in communication and miscommunication. Voigt's work has been published in diverse interdisciplinary venues such as the Journal of Sociolinguistics, the Proceedings of the National Academy of Sciences, and Sociological Science in addition to fundamental contributions to discipline-specific venues associated with the Association for Computational Linguistics. His work on analyzing police language from body camera footage in particular has received multiple awards including the Cozzarelli Prize for best paper in the behavioral and social sciences at PNAS in 2017.

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