论文标题
多语言和跨语言议会语音分析
Multi-aspect Multilingual and Cross-lingual Parliamentary Speech Analysis
论文作者
论文摘要
议会和立法辩论的成绩单为当选政客的意见，立场和政策偏好提供了信息丰富的见解。对于政治和社会科学以及语言学和自然语言处理（NLP）研究，它们都很有趣。在现有的研究研究各个议会的同时，我们将高级NLP方法应用于2017年至2020年之间的六个国家议会（保加利亚，捷克，法语，斯洛文尼亚，西班牙和英国）的共同和比较分析。我们分析了来自Parlamint数据集收集的转录中的情感和情感，并评估年龄的年龄，并评估年龄的言论，以表达他们的性格，政治和政治范围。结果表明，被分析国家之间的一些共同点和许多令人惊讶的差异。
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.
