@misc{10481/89164,
year = {2023},
url = {https://hdl.handle.net/10481/89164},
abstract = {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.},
organization = {COST (European Cooperation in Science and Technology)},
organization = {Slovenian Research
Agency  P6-0411, J6-2581, J7-3159, V5-2297},
organization = {European Social Fund},
organization = {Andalusian Government},
organization = {University of Granada (A-HUM-250-UGR18 & P18-FR-5020)},
organization = {CLaDA-BG DO01-377/18.12.2020},
keywords = {Parliamentary debates},
keywords = {Natural language processing},
keywords = {Deep learning},
keywords = {Topic modelling},
title = {Multi-aspect multilingual and cross-lingual parliamentary speech analysis},
doi = {10.3233/ida-227347},
author = {Miok, Kristian and Hidalgo Tenorio, Encarnación and Osenova, Petya and Benítez Castro, Miguel Ángel and Robnik-Šikonja, Marko},
}