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      Playing to the Gallery: Emotive Rhetoric in Parliaments

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          Abstract

          Research has shown that emotions matter in politics, but we know less about when and why politicians use emotive rhetoric in the legislative arena. This article argues that emotive rhetoric is one of the tools politicians can use strategically to appeal to voters. Consequently, we expect that legislators are more likely to use emotive rhetoric in debates that have a large general audience. Our analysis covers two million parliamentary speeches held in the UK House of Commons and the Irish Parliament. We use a dictionary-based method to measure emotive rhetoric, combining the Affective Norms for English Words dictionary with word-embedding techniques to create a domain-specific dictionary. We show that emotive rhetoric is more pronounced in high-profile legislative debates, such as Prime Minister’s Questions. These findings contribute to the study of legislative speech and political representation by suggesting that emotive rhetoric is used by legislators to appeal directly to voters.

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          Scikit-learn: Machine learning in Python

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            Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts

            Politics and political conflict often occur in the written and spoken word. Scholars have long recognized this, but the massive costs of analyzing even moderately sized collections of texts have hindered their use in political science research. Here lies the promise of automated text analysis: it substantially reduces the costs of analyzing large collections of text. We provide a guide to this exciting new area of research and show how, in many instances, the methods have already obtained part of their promise. But there are pitfalls to using automated methods—they are no substitute for careful thought and close reading and require extensive and problem-specific validation. We survey a wide range of new methods, provide guidance on how to validate the output of the models, and clarify misconceptions and errors in the literature. To conclude, we argue that for automated text methods to become a standard tool for political scientists, methodologists must contribute new methods and new methods of validation.
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              Scaling Policy Preferences from Coded Political Texts

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                Author and article information

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                Journal
                American Political Science Review
                Am Polit Sci Rev
                Cambridge University Press (CUP)
                0003-0554
                1537-5943
                May 24 2021
                : 1-15
                Article
                10.1017/S0003055421000356
                3fdab830-a733-42f2-adf4-5b7daf224898
                © 2021

                http://creativecommons.org/licenses/by/4.0/

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