Textual Data and NLP in Policy Process Research I

Abstract

Much policy-relevant, textual data remains unused as it is challenging to meaningfully operationalize in quantitative analysis or to exhaustively process in hand-coded qualitative analysis. The field of natural language processing (NLP) has developed rapidly and is increasingly used for public policy research. This panel creates knowledge on how advances in NLP help address this challenge and advance policy research.

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