通过语义框架分析，揭示不同政治立场如何用相同隐喻表达差异观点。
Not all ANIMALs are equal: metaphorical framing through source domains and semantic frames
- 结合源域与语义框架，构建隐喻分析计算模型。
- 发现保守派更倾向使用不可控框架，自由派倾向中立或受害者框架。
- 首次实现隐喻的细粒度跨意识形态对比，适合语言学与舆情研究者。
隐喻是强大的话语塑造工具，但其源域本身无法完全解释所引发的具体联想。我们提出，源域与语义框架的相互作用决定了隐喻如何塑造对复杂议题的理解，并构建了一个计算框架，可基于源域与语义框架推导出关键话语隐喻。将该框架应用于气候变化新闻，不仅识别出常见源域，还揭示了细微的框架级关联，展现议题表述的差异。在跨政治意识形态的移民议题分析中，我们发现保守派与自由派在相同源域中系统性采用不同语义框架：保守派偏好强调不可控性的框架，而自由派则选择中性或更具‘受害感’的框架。本研究连接概念隐喻理论与语言学，首次提供基于NLP的隐喻发现与精细分析方法。代码、数据与统计脚本见https://github.com/julia-nixie/ConceptFrameMet。
原文摘要 · Abstract (English)
Metaphors are powerful framing devices, yet their source domains alone do not fully explain the specific associations they evoke. We argue that the interplay between source domains and semantic frames determines how metaphors shape understanding of complex issues, and present a computational framework that allows to derive salient discourse metaphors through their source domains and semantic frames. Applying this framework to climate change news, we uncover not only well-known source domains but also reveal nuanced frame-level associations that distinguish how the issue is portrayed. In analyzing immigration discourse across political ideologies, we demonstrate that liberals and conservatives systematically employ different semantic frames within the same source domains, with conservatives favoring frames emphasizing uncontrollability and liberals choosing neutral or more ``victimizing'' semantic frames. Our work bridges conceptual metaphor theory and linguistics, providing the first NLP approach for discovery of discourse metaphors and fine-grained analysis of differences in metaphorical framing. Code, data and statistical scripts are available at https://github.com/julia-nixie/ConceptFrameMet.
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