---
title: "From Emotion to Expression — paper by Shankaran et al. (2026)"
description: "Fear speech is content that stokes fear of a group or threat. 74 references. Among them: 0."
authors: ["Vigneshwaran Shankaran", "Gabriella Lapesa", "Claudia Wagner"]
year: 2026
venue: "Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)"
source: "https://aclanthology.org/2026.eacl-long.118/"
doi: "10.18653/v1/2026.eacl-long.118"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/shankaran-2026-emotion-expression-theoretical-foundations-resources/"
---
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# From Emotion to Expression: Theoretical Foundations and Resources for Fear Speech

**Authors:** Vigneshwaran Shankaran, [Gabriella Lapesa](https://md.research.elamur.ai/free/en/authors/gabriella-lapesa/) and [Claudia Wagner](https://md.research.elamur.ai/free/en/authors/claudia-wagner/) · **Year:** 2026 · **Venue:** [Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)](https://md.research.elamur.ai/free/en/venues/eacl/) ([EACL 2026](https://md.research.elamur.ai/free/en/venues/eacl/2026/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2026.eacl-long.118/) · [PDF](https://aclanthology.org/2026.eacl-long.118.pdf) · [DOI 10.18653/v1/2026.eacl-long.118](https://doi.org/10.18653/v1/2026.eacl-long.118) · [OpenAlex](https://openalex.org/W7140105179)

**Citations:** 0 citations (OpenAlex, 2026-10-14)

## Summary
Fear speech is content that stokes fear of a group or threat. It can outspread hate speech because it sounds more civil and slips past moderation, yet NLP has mostly treated fear as one emotion label among many. The authors (GESIS) respond with a theory-and-survey paper rather than a new model. They compare how four disciplines understand fear:
- Political science: securitization and elite rhetoric
- Communication science: fear appeals, PMT, EPPM
- Psychology: emotion and appraisal
- Linguistics: metaphor, discourse, framing

They merge these views into a multilevel framework, starting with the source of fear and the message carrying it. Next, they review existing definitions of fear speech, select the most suitable one and extend it. Finally, they audit datasets from neighbouring fields whose labels partly capture fear and propose a taxonomy of fear dimensions. The audit finds these signals scattered unevenly, concentrated in computer-science work and thin on social-science perspectives. This gives practical guidance for reusing existing data instead of funding costly new annotation.

## Key points
- Fear speech is motivated by earlier evidence (Saha et al., 2023) that it is widespread, growing and often more engaging than hate speech.
- The disciplines frame fear differently:
  - Political science: a strategic tool of elites, via the Copenhagen School's securitization theory.
  - Communication science: a persuasion device that can be beneficial when paired with coping information, via PMT and EPPM.
  - Psychology: an internal, appraisal-driven emotion.
  - Linguistics: something built through metaphors and frames.
- The dataset survey covers adjacent phenomena that partially encode fear, such as propaganda ("appeal to fear"), framing ("immigrant as a threat"), fallacies, populism and abusive speech.
- The survey identifies several gaps:
  - Annotation practices are inconsistent.
  - Resources are concentrated in computational venues.
  - Language coverage is largely limited to English and German.
  - Guidelines and agreement reporting are often missing.
- The authors maintain a community-extendable catalogue of fear-relevant datasets at fearspeechdata.com, which accepts additions via pull requests.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

## Institutions

- [Heinrich Heine University Düsseldorf](https://md.research.elamur.ai/free/en/universities/heinrich-heine-university-dusseldorf/) — University, Düsseldorf, Germany · 34 works · 1,487 citations
- [GESIS - Leibniz Institute for the Social Sciences](https://md.research.elamur.ai/free/en/labs/gesis-leibniz-institute-for-the-social-sciences/) — Research institute, Mannheim, Germany · 10 works · 5 citations

📚 Shelves (4): [🖥️ Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) · 18,614 works · [🤖 Artificial Intelligence](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · 17,965 works · [🤝 Social Sciences](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · 1,954 works · [🤝 Sociology and Political Science](https://md.research.elamur.ai/free/en/shelves/social-sciences/sociology-and-political-science/) · 626 works

🧭 Topics (1): [😊 Sentiment & emotion](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · 1,035 works

## Cite

Cite as: Vigneshwaran Shankaran, Gabriella Lapesa and Claudia Wagner. 2026. From Emotion to Expression: Theoretical Foundations and Resources for Fear Speech. Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers).

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{shankaran2026emotion,
  title = {{From Emotion to Expression: Theoretical Foundations and Resources for Fear Speech}},
  author = {Vigneshwaran Shankaran, Gabriella Lapesa and Claudia Wagner},
  booktitle = {Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2026},
  doi = {10.18653/v1/2026.eacl-long.118},
  url = {https://doi.org/10.18653/v1/2026.eacl-long.118}
}
```

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*Updated 2 November 2026*