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Emotion and Reason in Political Language
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In: The Economic Journal, 132 (643) (2022)
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Abstract:
This paper studies the use of emotion and reason in political discourse. Adopting computational-linguistics techniques to construct a validated text-based scale, we measure emotionality in 6 million speeches given in U.S. Congress over the years 1858-2014. Intuitively, emotionality spikes during times of war and is highest in speeches about patriotism. In the time series, emotionality was relatively low and stable in earlier years but increased significantly starting in the late 1970s. Across Congress Members, emotionality is higher for Democrats, for women, for ethnic/religious minorities, for the opposition party, and for members with ideologically extreme roll-call voting records. ; ISSN:0013-0133 ; ISSN:1468-0297
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Keyword:
Emotions; Political Rhetoric; U.S. Congress; Word Embeddings
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URL: https://hdl.handle.net/20.500.11850/533392
https://doi.org/10.3929/ethz-b-000533392
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| 4 |
Text Semantics Capture Political and Economic Narratives ...
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| 5 |
Text Semantics Capture Political and Economic Narratives
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In: Center for Law & Economics Working Paper Series, 2021 (11) (2021)
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| 6 |
Dimensions of Mind in Semantic Space
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In: Center for Law & Economics Working Paper Series, 2021 (14) (2021)
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| 7 |
Machine Extraction of Tax Laws from Legislative Texts
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In: Proceedings of the Natural Legal Language Processing Workshop 2021 (2021)
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| 8 |
Automated fact-value distinction in court opinions
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In: ISSN: 0929-1261 ; EISSN: 1572-9990 ; European Journal of Law and Economics ; https://hal.archives-ouvertes.fr/hal-03174376 ; European Journal of Law and Economics, Springer Verlag, 2020, 50 (3), pp.451-467. ⟨10.1007/s10657-020-09645-7⟩ (2020)
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| 9 |
Unsupervised Extraction of Workplace Rights and Duties from Collective Bargaining Agreements ...
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| 12 |
Unsupervised Extraction of Workplace Rights and Duties from Collective Bargaining Agreements
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In: 2020 International Conference on Data Mining Workshops (ICDMW) (2020)
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| 13 |
More Laws, More Growth? Evidence from U.S. States
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In: Center for Law & Economics Working Paper Series, 15/2020 (2020)
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| 14 |
Automated fact-value distinction in court opinions
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In: European Journal of Law and Economics, 50 (3) (2020)
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| 15 |
Stereotypes in High-Stakes Decisions : Evidence from U.S. Circuit Courts
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| 16 |
Stereotypes in High-Stakes Decisions : Evidence from U.S. Circuit Courts
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