---
title: "Social Story Frames — paper by Mire et al. (2026)"
description: "This paper proposes SOCIAL STORY FRAMES, a formalism that models plausible reader responses… 112 references, cited by 1 paper here."
authors: ["Joel Mire", "Maria Antoniak", "Steven R Wilson", "Zexin Ma", "Achyutarama R Ganti", "Andrew Piper", "Maarten Sap"]
year: 2026
venue: "Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)"
source: "https://aclanthology.org/2026.acl-long.1934/"
doi: "10.18653/v1/2026.acl-long.1934"
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/mire-2026-social-story-frames-contextual-reasoning/"
---
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# Social Story Frames: Contextual Reasoning about Narrative Intent and Reception

**Authors:** Joel Mire, [Maria Antoniak](https://md.research.elamur.ai/free/en/authors/maria-antoniak/), Steven R Wilson, Zexin Ma, Achyutarama R Ganti, [Andrew Piper](https://md.research.elamur.ai/free/en/authors/andrew-piper/) and [Maarten Sap](https://md.research.elamur.ai/free/en/authors/maarten-sap/) · **Year:** 2026 · **Venue:** [Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)](https://md.research.elamur.ai/free/en/venues/acl/) ([ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/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.acl-long.1934/) · [PDF](https://aclanthology.org/2026.acl-long.1934.pdf) · [DOI 10.18653/v1/2026.acl-long.1934](https://doi.org/10.18653/v1/2026.acl-long.1934) · [OpenAlex](https://openalex.org/W4417534162)

**Citations:** 0 citations (OpenAlex, 2026-10-14) · 1 in our library, of the 149,439 papers whose bibliographies we read

## Summary
Stories posted online provoke many kinds of reader reactions, such as guesses about why the author is sharing, emotional responses, and moral judgments of characters. Existing computational methods either study single communities in depth or measure storytelling only coarsely at scale. This paper proposes SOCIAL STORY FRAMES, a formalism that models plausible reader responses to a story while taking into account the community and the surrounding conversation. Its taxonomy, SSF-TAXONOMY, draws on narrative theory, pragmatics, and psychology and covers 10 response dimensions. The authors build a two-stage pipeline. SSF-GENERATOR produces free-text inferences, and SSF-CLASSIFIER assigns those inferences to fine-grained taxonomy subcategories. Both models were trained by distilling outputs from GPT models. The authors validated the pipeline with crowd surveys and expert annotation, then applied it to SSF-CORPUS, a collection of Reddit stories. They describe how often different storytelling intents occur and how those intents relate to each other, and they compare narrative practices across subreddits. Some communities with unrelated topics turn out to use stories in socially similar ways. This makes it possible to compare storytelling across many communities without losing interpretive detail.

## Key points
- SSF-TAXONOMY has 10 dimensions, grouped into four kinds of response:
  - inferences about the author: overall goal, narrative intent, and author emotion;
  - explanatory and predictive inferences: causal explanation and prediction;
  - value judgments, such as character appraisal;
  - affective reader responses, such as suspense, curiosity, and absorption.
- SSF-GENERATOR was trained with supervised fine-tuning to distill GPT-4o, and SSF-CLASSIFIER was distilled from GPT-4.1. Classification quality was checked with expert annotations.
- The human surveys involved 382 participants in total. Of these, 278 assessed inferences used as the classifier's training data, and 104 rated model outputs.
- SSF-CORPUS contains 6,140 English social media stories with their conversational context, drawn from many subreddits. Highly toxic and sexually explicit content and PII were removed.
- Storytelling in topically different communities can follow similar social patterns (e.g., r/MakeupAddiction and r/buildapc), which semantic similarity alone does not capture; the comparison uses an ssf-sim metric. The models are released on HuggingFace, and users must first acknowledge the stated limitations, which include English only and a U.S. annotator pool.

*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

- [Carnegie Mellon University](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) — University, Pittsburgh, United States · 539 works · 179,533 citations
- [University of Colorado Boulder](https://md.research.elamur.ai/free/en/universities/university-of-colorado-boulder/) — University, Boulder, United States · 69 works · 51,069 citations
- [McGill University](https://md.research.elamur.ai/free/en/universities/mcgill-university/) — University, Montreal, Canada · 87 works · 11,027 citations
- [University of Connecticut](https://md.research.elamur.ai/free/en/universities/university-of-connecticut/) — University, Storrs, United States · 11 works · 357 citations

Also on the byline: [University of Michigan–Flint](https://ror.org/01c3xc117).

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🧭 Topics (1): [🧮 Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/) · 1,426 works

## Cite

Cite as: Joel Mire, Maria Antoniak, Steven R Wilson, Zexin Ma, Achyutarama R Ganti, Andrew Piper and Maarten Sap. 2026. Social Story Frames: Contextual Reasoning about Narrative Intent and Reception. Proceedings of the 64th Annual Meeting 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{mire2026social,
  title = {{Social Story Frames: Contextual Reasoning about Narrative Intent and Reception}},
  author = {Joel Mire, Maria Antoniak, Steven R Wilson, Zexin Ma, Achyutarama R Ganti, Andrew Piper and Maarten Sap},
  booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2026},
  doi = {10.18653/v1/2026.acl-long.1934},
  url = {https://doi.org/10.18653/v1/2026.acl-long.1934}
}
```

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*Updated 31 October 2026*