Abstract
In Conceptual Metaphor Theory (CMT), a metaphor is a systematic mapping from a concrete source domain (e.g., physical load) to a more abstract target domain (e.g., taxes), so that reasoning about concepts in the target domain is guided by inferences from the source domain. In this work, we propose that since different source domains can frame the same target in starkly different ways, the conceptual mappings evidenced by metaphorical expressions can guide computational political discourse analysis. We present a proof-of-concept for an unsupervised method that uncovers salient conceptual mappings from a corpus. Prior work in computational political metaphor analysis has drawn on CMT, but it typically requires a predetermined inventory of focused source and target domains. In contrast, we introduce a simple LLM-based method that detects metaphorical expressions from a corpus with strong performance, then clusters them to approximate source domain categories. We demonstrate its utility through a case study on online immigration discourse, showing that the resulting metaphor clusters provide context for frame analysis. We conclude by outlining future work needed to develop a robust framework for conceptual metaphor discovery in political discourse.- Anthology ID:
- 2026.nlpcss-1.11
- Volume:
[Proceedings of the Seventh Workshop on Natural Language Processing and Computational Social Science](/volumes/2026.nlpcss-1/)- Month:
- July
- Year:
- 2026
- Address:
- San Diego
- Editors:
[Dallas Card](/people/dallas-card/),[Anjalie Field](/people/anjalie-field/),[Katherine Keith](/people/katherine-keith/),[Julia Mendelsohn](/people/julia-mendelsohn/)- Venues:
[NLP+CSS](/venues/nlpcss/)|[WS](/venues/ws/)- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 159–175
- Language:
- URL:
[https://aclanthology.org/2026.nlpcss-1.11/](https://aclanthology.org/2026.nlpcss-1.11/)- DOI:
[10.18653/v1/2026.nlpcss-1.11](https://doi.org/10.18653/v1/2026.nlpcss-1.11)- Cite (ACL):
- Alexandria Leto and Maria Leonor Pacheco. 2026. Toward Unsupervised Conceptual Metaphor Discovery: A Case Study in Online Immigration Discourse. InProceedings of the Seventh Workshop on Natural Language Processing and Computational Social Science, pages 159–175, San Diego. Association for Computational Linguistics. - Cite (Informal):
[Toward Unsupervised Conceptual Metaphor Discovery: A Case Study in Online Immigration Discourse](https://aclanthology.org/2026.nlpcss-1.11/)(Leto & Pacheco, NLP+CSS 2026)- PDF:
[https://aclanthology.org/2026.nlpcss-1.11.pdf](https://aclanthology.org/2026.nlpcss-1.11.pdf)