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.

翻译：NLP+CSS领域的研究几乎仅基于左/右党派轴对意识形态进行操作化。这种做法掩盖了一个事实：人们在种族、气候、性别等问题上往往持有多种不同复杂且更具特异性的意识形态解读。我们提出一个将意识形态理解为归因性、多层次的社会认知概念网络的框架，并阐释意识形态如何在与框架化等其他相关社会过程的关系中通过话语得以显现。我们论证了该框架如何厘清现有NLP任务（如立场检测与自然语言推理）之间的重叠，同时揭示新的研究方向。本项工作为计算方法与意识形态理论搭建了独特而重要的桥梁，从而以惠及两个领域的方式实现对社会议话语更丰富的分析。