用道德理论分析推特政治话题演化，揭示持久话题的道德根源。
Modeling Political Discourse with Sentence-BERT and BERTopic
- 结合BERTopic与道德基础理论，追踪推特话题随时间演变。
- 核心话题稳定但细粒度话题迅速消散，道德价值决定话题寿命。
- 适合研究政治极化、社交媒体传播与计算社会科学者阅读。
社交媒体重塑了政治话语，为政客提供直接互动平台的同时也加剧了分化。本研究提出一种融合BERTopic主题建模与道德基础理论（MFT）的话题演化分析框架，用于研究美国第117届国会期间推特上政治话题的持续性与道德维度。通过方法论设计实现动态话题追踪，并量化其与道德价值的关联及持久性。研究发现：虽然宏观主题保持稳定，但细粒度话题往往快速消散，难以产生长期影响；道德基础在话题持久性中起关键作用，关怀（Care）与忠诚（Loyalty）主导持久话题，而党派差异体现于不同的道德叙事策略。该工作为社交网络分析与计算政治话语研究提供了可扩展、可解释的分析路径。
原文摘要 · Abstract (English)
Social media has reshaped political discourse, offering politicians a platform for direct engagement while reinforcing polarization and ideological divides. This study introduces a novel topic evolution framework that integrates BERTopic-based topic modeling with Moral Foundations Theory (MFT) to analyze the longevity and moral dimensions of political topics in Twitter activity during the 117th U.S. Congress. We propose a methodology for tracking dynamic topic shifts over time and measuring their association with moral values and quantifying topic persistence. Our findings reveal that while overarching themes remain stable, granular topics tend to dissolve rapidly, limiting their long-term influence. Moreover, moral foundations play a critical role in topic longevity, with Care and Loyalty dominating durable topics, while partisan differences manifest in distinct moral framing strategies. This work contributes to the field of social network analysis and computational political discourse by offering a scalable, interpretable approach to understanding moral-driven topic evolution on social media.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。