当话语产生分歧：社交媒体政治讨论中的历时意识形态极化
When Words Divide: Diachronic Ideological Polarization in Political Discourse on Social Media
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中文总结 AI 辅助
该研究通过构建时间对齐的Reddit社群特定词嵌入，量化政治概念的语义差异以分析意识形态极化，发现研究期间极化大幅加剧，其方法可捕捉语义框架中意识形态差异的演变。
中文摘要 AI 辅助
政治极化已成为网络话语的一个核心特征，但其长期演变仍鲜为人知。我们通过测量对立政治社群所用语言的语义差异，对Reddit讨论中的意识形态极化进行纵向分析。我们构建时间对齐的社群特定词嵌入，并将意识形态极化量化为政治概念随时间的语义差异。分析显示，在研究期间，无论是概念层面还是主题层面，意识形态极化都大幅加剧。与以往计算工作多聚焦于某一时点的横断面分析或极化的情感维度不同，我们的方法捕捉了语义框架中意识形态差异的演变。所提出的框架为研究大规模社交媒体话语中意识形态极化的时间动态提供了可扩展的方法。
英文摘要
Political polarization has become a defining feature of online discourse, yet its long-term evolution remains poorly understood. We present a longitudinal analysis of ideological polarization in Reddit discussions by measuring semantic differences in the language used by opposing political communities. We construct temporally aligned community-specific word embeddings and quantify ideological polarization as the semantic divergence of political concepts over time. Our analysis shows that ideological polarization has increased substantially during the study period, both at the concept- and topic-level. Unlike prior computational work, which has largely focused on cross-sectional analyses or affective dimensions of polarization at a single point at time, our approach captures the evolution of ideological differences in semantic framing. The proposed framework provides a scalable method for studying the temporal dynamics of ideological polarization in large-scale social media discourse.
发表机构
- The Academic College of Tel-Aviv Yaffo（特拉维夫-雅法学术学院）
机构由 AI 辅助整理，请以论文原文为准。
