---
title: "Exploring Subjective Tasks in Farsi: A Survey Analysis and"
description: "The authors argue that this label breaks down for subjective NLP. 38 references. Among them: 0."
authors: ["Donya Rooein", "Flor Miriam Plaza-del-Arco", "Debora Nozza", "Dirk Hovy"]
year: 2026
venue: "The Proceedings for the 15th Workshop on Computational Approaches to Subjectivity, Sentiment Social Media Analysis (WASSA 2026)"
source: "https://aclanthology.org/2026.wassa-1.8/"
doi: "10.18653/v1/2026.wassa-1.8"
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/rooein-2026-exploring-subjective-tasks-farsi-survey/"
---
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# Exploring Subjective Tasks in Farsi: A Survey Analysis and Evaluation of Language Models

**Authors:** [Donya Rooein](https://md.research.elamur.ai/free/en/authors/donya-rooein/), Flor Miriam Plaza-del-Arco, [Debora Nozza](https://md.research.elamur.ai/free/en/authors/debora-nozza/) and [Dirk Hovy](https://md.research.elamur.ai/free/en/authors/dirk-hovy/) · **Year:** 2026 · **Venue:** [The Proceedings for the 15th Workshop on Computational Approaches to Subjectivity, Sentiment Social Media Analysis (WASSA 2026)](https://md.research.elamur.ai/free/en/venues/wassa/) ([Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis 2026](https://md.research.elamur.ai/free/en/venues/wassa/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.wassa-1.8/) · [PDF](https://aclanthology.org/2026.wassa-1.8.pdf) · [DOI 10.18653/v1/2026.wassa-1.8](https://doi.org/10.18653/v1/2026.wassa-1.8) · [OpenAlex](https://openalex.org/W7140123715)

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

## Summary
Farsi has more than 127 million speakers and a large online presence, which would suggest a "middle-resource" status. The authors argue that this label breaks down for subjective NLP. They survey work on sentiment analysis (SA), emotion analysis (EA) and toxicity detection (TD). They ran 140 structured keyword queries over the ACL Anthology and Google Scholar (via SerpApi) and manually annotated the resulting 110 papers. The annotation extends the Plaza-del Arco et al. (2024) framework with lexicon use, classification type, annotator demographics and dataset availability.

They then compared fine-tuned encoders (XLM-RoBERTa, FaBERT) with zero-shot open-source LLMs on the few public datasets. They also examined machine translation into English as a workaround.

The survey found few publicly available datasets. Most come from tweets or Digikala product reviews, and they rarely record annotator age or gender. Scores fluctuate strongly across datasets and models. Fine-tuning gives the best results on every task, LLMs come closest on TD, and they are weakest on EA. The broader lesson is that raw text volume does not make a language well-resourced for subjective tasks.

## Key points
- **Corpus of reviewed papers:**
  - 110 papers from 2006–2025, with searches updated to March 2025.
  - By task: 58 SA, 36 EA and 16 TD.
  - By source: only 12 come from the ACL Anthology, and none of those cover TD. The remaining 98 include 40 from arXiv, 16 from IEEE and 12 from Springer.
- **Emotion datasets:** seven EA datasets were identified, including ShortPersianEmo and SAT. ShEMO (3,000 samples from radio plays) is the only one combining text and speech.
- **Model evaluation datasets:** MirasOpinion, SentiPars and ParsABSA (SA), and Pars-OFF and PHICAD (TD), among others.
- **Toxicity results (average macro F1):** FaBERT scores 0.896, XLM-RoBERTa 0.851 and zero-shot Qwen2-7B 0.809. Qwen2-7B even beats XLM-RoBERTa on Pars-OFF and PHICAD.
- **Sentiment results:** fine-tuned XLM-RoBERTa averages 0.758 and outperforms the LLMs. FaBERT is inconsistent: strong on MirasOpinion and SentiPars, weaker on ParsABSA.

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

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## Cite

Cite as: Donya Rooein, Flor Miriam Plaza-del-Arco, Debora Nozza and Dirk Hovy. 2026. Exploring Subjective Tasks in Farsi: A Survey Analysis and Evaluation of Language Models. The Proceedings for the 15th Workshop on Computational Approaches to Subjectivity, Sentiment Social Media Analysis (WASSA 2026).

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

```bibtex
@inproceedings{rooein2026exploring,
  title = {{Exploring Subjective Tasks in Farsi: A Survey Analysis and Evaluation of Language Models}},
  author = {Donya Rooein, Flor Miriam Plaza-del-Arco, Debora Nozza and Dirk Hovy},
  booktitle = {The Proceedings for the 15th Workshop on Computational Approaches to Subjectivity, Sentiment Social Media Analysis (WASSA 2026)},
  year = {2026},
  doi = {10.18653/v1/2026.wassa-1.8},
  url = {https://doi.org/10.18653/v1/2026.wassa-1.8}
}
```

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*Updated 1 November 2026*