用 BERT 模型预测党派归属以分析奥地利议会演讲
Analysing Austrian Parliamentary Speeches by Predicting Party Affiliations
AI 导读
研究者用微调后的 BERT 模型为奥地利国民议会每位议员的演讲预测党派归属概率分布，并在议员和党派层面聚合。分析发现联合执政的政党演讲特征趋于相似，反对党则远离执政党，而转党的议员通常在转党之后才改变演讲特征。研究还公开发布了 1996 至 2018 年演讲党派归属预测数据集。
正文 · 原文
Abstract:This paper examines speech characteristics of the Austrian National Council members (CMs). We introduce analysis methodology based on a fine-tuned BERT-Model which assigns to every speech a probability distribution over Austrian parties. These are then aggregated at the speaker and party level. We perform an extensive evaluation to ensure the quality of the generated distributions prior to further analysis. Instead of considering mis-assignments of predicted parties as a performance issue, we leverage them to derive insights about the CMs and political developments. Our findings show that parties that govern together become more similar in their speech characteristics, while, analogously, parties that are in opposition move further away from governing parties. Moreover, CMs who switch party usually adapt their speech characteristics only after the switch occurs. Finally, we publicly release a data set containing party affiliation predictions for the speeches of the Austrian National Council from 1996 to 2018.
| Comments: | KONVENS 2026 |
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Machine Learning (cs.LG) |
| ACM classes: | I.2.7; I.7.0; J.4 |
| Cite as: | arXiv:2610.32515 [cs.CL] |
| (or arXiv:2610.32515v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2610.32515 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Sarah Sulollari [view email]
[v1]
Fri, 23 Oct 2026 11:38:35 UTC (676 KB)
来源：arXiv cs.AI · arxiv.org