Multi-aspect Multilingual and Cross-lingual Parliamentary Speech Analysis
This work provides comparative insights for political science, linguistics, and NLP researchers, but is incremental as it extends existing methods to new multilingual data.
The study applied NLP methods to analyze parliamentary speech transcripts from six countries, finding both commonalities and surprising differences in emotions, sentiment, and speaker attributes like age, gender, and political orientation.
Parliamentary and legislative debate transcripts provide 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 existing 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.