提出多层级意识形态网络框架，突破左右政治光谱局限
A conceptual framework for ideology beyond the left and right
- 将意识形态视为多层次认知网络，融合社会认知与话语分析
- 揭示立场识别与自然语言推理任务间的内在关联与重叠
- 为计算社会科学与意识形态理论提供交叉研究新范式
自然语言处理与计算社会科学研究中，意识形态的建模几乎完全基于左右政治光谱。然而这一方法忽视了人们在种族、气候、性别等议题上持有的复杂且具体的多元意识形态。本文提出一种框架，将意识形态理解为一种被赋予的、多层次的社会认知概念网络，并阐释其如何通过框架化等社会过程在话语中显现。该框架不仅厘清了现有NLP任务（如立场检测与自然语言推理）之间的联系，还揭示了新的研究方向。本工作在计算方法与意识形态理论之间搭建起独特桥梁，推动社会话语分析向更丰富、更深入的方向发展。
原文摘要 · Abstract (English)
NLP+CSS work has operationalized ideology almost exclusively on a left/right partisan axis. This approach obscures the fact that people hold interpretations of many different complex and more specific ideologies on issues like race, climate, and gender. We introduce a framework that understands ideology as an attributed, multi-level socio-cognitive concept network, and explains how ideology manifests in discourse in relation to other relevant social processes like framing. We demonstrate how this framework can clarifies overlaps between existing NLP tasks (e.g. stance detection and natural language inference) and also how it reveals new research directions. Our work provides a unique and important bridge between computational methods and ideology theory, enabling richer analysis of social discourse in a way that benefits both fields.
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