Multi-aspect multilingual and cross-lingual parliamentary speech analysis
Metadatos
Mostrar el registro completo del ítemAutor
Miok, Kristian; Hidalgo Tenorio, Encarnación; Osenova, Petya; Benítez Castro, Miguel Ángel; Robnik-Šikonja, MarkoMateria
Parliamentary debates Natural language processing Deep learning Topic modelling
Fecha
2023Referencia bibliográfica
Published version: Miok, Kristian et al. ‘Multi-aspect Multilingual and Cross-lingual Parliamentary Speech Analysis’. 1 Jan. 2023 : 1 – 22. https://doi.org/10.3233/ida-227347
Patrocinador
COST (European Cooperation in Science and Technology); Slovenian Research Agency P6-0411, J6-2581, J7-3159, V5-2297; European Social Fund; Andalusian Government; University of Granada (A-HUM-250-UGR18 & P18-FR-5020); CLaDA-BG DO01-377/18.12.2020Resumen
Parliamentary and legislative debate transcripts provide an informative insight into elected politicians’ opinions, positions,
and policy preferences. They are interesting for political and social sciences as well as linguistics and natural language processing (NLP) research. While exiting research studied individual parliaments, we apply advanced NLP methods to a joint and
comparative analysis of six national parliaments (Bulgarian, Czech, French, Slovene, Spanish, and United Kingdom) between
2017 and 2020. We analyze emotions and sentiment in the transcripts from the ParlaMint dataset collection, and assess if the
age, gender, and political orientation of speakers can be detected from their speeches. The results show some commonalities
and many surprising differences among the analyzed countries.