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Nick Beauchamp, Ph.D. (NYU) and lecturer at Columbia

Political opinion forms in the torrent of language surrounding all of us, but despite the recent proliferation of speech and social network data, existing models of political persuasion and communication remain rooted in simplistic frameworks of low-dimensional ideological spaces and basic expressive or information-transmitting speech. This work instead develops new techniques in automated text analysis and large-scale causal inference to model the complex interplay between speech, belief, and political behaviors.