Natural Language Processing for Policymaking

Author:

Jin Zhijing,Mihalcea Rada

Abstract

AbstractLanguage is the medium for many political activities, from campaigns to news reports. Natural language processing (NLP) uses computational tools to parse text into key information that is needed for policymaking. In this chapter, we introduce common methods of NLP, including text classification, topic modelling, event extraction, and text scaling. We then overview how these methods can be used for policymaking through four major applications including data collection for evidence-based policymaking, interpretation of political decisions, policy communication, and investigation of policy effects. Finally, we highlight some potential limitations and ethical concerns when using NLP for policymaking.

Funder

The European Union, represented by the European Commission

Publisher

Springer International Publishing

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