Multi-aspect multilingual and cross-lingual parliamentary speech analysis Miok, Kristian Hidalgo Tenorio, Encarnación Osenova, Petya Benítez Castro, Miguel Ángel Robnik-Šikonja, Marko Parliamentary debates Natural language processing Deep learning Topic modelling This work is based upon the collaboration in the COST Action CA18209 – NexusLinguarum “European network for Web-centred linguistic data science”, supported by COST (European Cooperation in Sci- ence and Technology). Marko Robnik-Šikonja received financial support from the Slovenian Research Agency through core research programme P6-0411 and projects J6-2581, J7-3159, and V5-2297. Encar- nación Hidalgo Tenorio was financially supported by the European Social Fund, the Andalusian Gov- ernment, and the University of Granada (Project References: A-HUM-250-UGR18 & P18-FR-5020). Petya Osenova was partially supported by CLaDA-BG, the Bulgarian National Interdisciplinary Re- search e-Infrastructure for Resources and Technologies in favor of the Bulgarian Language and Cultural Heritage, and partially through the EU infrastructures CLARIN and DARIAH, Grant number DO01- 377/18.12.2020. 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. 2024-02-14T11:03:35Z 2024-02-14T11:03:35Z 2023 journal article 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 https://hdl.handle.net/10481/89164 10.3233/ida-227347 eng open access