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A data science approach to 138 years of congressional speeches.
Tucker, Ethan C; Capps, Colton J; Shamir, Lior.
Afiliación
  • Tucker EC; Department of Computer Science, Kansas State University, Manhattan KS 66502, USA.
  • Capps CJ; Department of Computer Science, Kansas State University, Manhattan KS 66502, USA.
  • Shamir L; Department of Computer Science, Kansas State University, Manhattan KS 66502, USA.
Heliyon ; 6(8): e04417, 2020 Aug.
Article en En | MEDLINE | ID: mdl-32904137
ABSTRACT
The availability of automatic data analysis tools and large databases have enabled new ways of studying language and communication that were not possible in the pre-information era. Here we apply a quantitative analysis to a large dataset of USA congressional speeches made over a period of 138 years. The analysis reveals that the readability index of congressional speeches increased consistently until the 96th congress, and then started to decline. Congressional speeches have also become more positive over time, and in general express more sentiments compared to speeches made in the 19th century or early 20th century. The analysis also shows statistically significant differences between Democratic and Republican congressional speeches.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos