---
title: "Toward Culturally-Aware Arabic Debate Platforms with NLP"
description: "Arabic-speaking communities have few online spaces for structured, reasoned debate. 24 references."
authors: ["Khalid Al Khatib", "Mohammad Khader"]
year: 2025
venue: "Proceedings of The Third Arabic Natural Language Processing Conference"
source: "https://aclanthology.org/2025.arabicnlp-main.29/"
doi: "10.18653/v1/2025.arabicnlp-main.29"
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/khatib-2025-culturally-aware-arabic-debate-platforms/"
---
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# Toward Culturally-Aware Arabic Debate Platforms with NLP Support

**Authors:** [Khalid Al Khatib](https://md.research.elamur.ai/free/en/authors/khalid-al-khatib/) and Mohammad Khader · **Year:** 2025 · **Venue:** [Proceedings of The Third Arabic Natural Language Processing Conference](https://md.research.elamur.ai/free/en/venues/arabicnlp/) ([ArabicNLP 2025](https://md.research.elamur.ai/free/en/venues/arabicnlp/2025/)) · **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/2025.arabicnlp-main.29/) · [PDF](https://aclanthology.org/2025.arabicnlp-main.29.pdf) · [DOI 10.18653/v1/2025.arabicnlp-main.29](https://doi.org/10.18653/v1/2025.arabicnlp-main.29) · [OpenAlex](https://openalex.org/W4416037676)

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

## Summary
Arabic-speaking communities have few online spaces for structured, reasoned debate. Most existing tools are built around English and Western norms. The authors take a first step toward an NLP-supported debate platform that fits Arab cultural values, and they combine four strands of work:

- **Survey:** 62 questions, answered by 50 native Arabic speakers recruited through Prolific, on their past use of debate tools and their attitudes toward AI assistance.
- **Topic audit:** about 30,000 English debate topics from sites such as Kialo, iDebate and DebateData, rated by three LLMs with different cultural backgrounds (Fanar, DeepSeek, Claude) for cultural specificity and appropriateness.
- **Topic generation:** an exploration of whether LLMs can write new topics that resonate with Arab audiences.
- **Blueprint:** the NLP components such a platform would need.

Respondents want AI-assisted structured debate, but with limited AI involvement and strong cultural sensitivity. Imported topics seldom address Arab-specific issues, while LLM-generated topics look promising. The paper also frames culture-aware topic assessment and generation as a new research task.

## Key points
- The survey had four parts: general usage, engagement (split by prior experience), expectations about AI, and open feedback. All 50 participants finished it, in about 10 minutes 40 seconds on average.
- Participants valued topic discovery, voting and AI-generated arguments. They worried about AI errors, cultural insensitivity, loss of human agency, and hostile or judgmental tone.
- Topic sources included DebateData, Kialo Edu Blog, Kialo Edu Topics Library, iDebate Debatabase, I Side With and Britannica ProCon. The three judge models were chosen to reflect different perspectives: Arab-aligned (Fanar), Chinese (DeepSeek) and Western (Claude).
- The proposed pipeline has six parts:
  - argument mining;
  - evidence-type detection;
  - LLM topic and argument generation with expert curation;
  - cultural-fit classifiers;
  - human value detection, localizing the Touché taxonomy;
  - culture-aware counterargument generation.
- Related Arabic resources cited include Munazarat 1.0 (about 50 hours, 73 debates), QCAW 1.0 (195 essays), AraBERT and MARBERT. The paper's resources are released on GitHub (Arabic-Argument-Mining/ArabicNLP25).

## Interesting ideas
- Have several models with deliberately different cultural priors judge the same item, so their disagreement exposes judgments that depend on perspective rather than on fact.
- Rate content on two separate axes, specificity to a culture and appropriateness for it, rather than collapsing them into one "fit" score.
- Let LLMs bootstrap content in a low-resource setting, then run the same checker over machine-generated and user-submitted items before experts curate them.
- Label each argument's support by evidence type, such as testimony versus anecdote, so a reader can judge how strong the claim is.
- Detect which human values (tradition, humility, hedonism, etc.) an argument appeals to, using an existing taxonomy adapted locally.

## For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

- **I1** (learn): Witness parsers could be picked for different training biases (e.g., different treebanks), and the arcs where they split could be sent to review instead of entering silver data.
- **I2** (world): Knowledge-graph facts and values could carry a separate scope tag (which community or context they hold for), distinct from their truth or confidence.
- **I3** (answer): Generated test questions about fables could pass through the same validator that checks user questions, so both sources face one consistent filter.
- **I4** (frames): Speech-act analysis could attach a support-type slot to assertions, which helps separate reported claims from attested ones when answering.
- **I5** (frames): A value-appeal layer over frames would make persuasive or ironic passages easier to explain, by showing which value a speaker invokes.

*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

- [University of Groningen](https://md.research.elamur.ai/free/en/universities/university-of-groningen/) — University, Groningen, Netherlands · 74 works · 5,142 citations

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## Cite

Cite as: Khalid Al Khatib and Mohammad Khader. 2025. Toward Culturally-Aware Arabic Debate Platforms with NLP Support. Proceedings of The Third Arabic Natural Language Processing Conference.

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

```bibtex
@inproceedings{khatib2025toward,
  title = {{Toward Culturally-Aware Arabic Debate Platforms with NLP Support}},
  author = {Khalid {Al Khatib} and Mohammad Khader},
  booktitle = {Proceedings of The Third Arabic Natural Language Processing Conference},
  year = {2025},
  doi = {10.18653/v1/2025.arabicnlp-main.29},
  url = {https://doi.org/10.18653/v1/2025.arabicnlp-main.29}
}
```

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## References

24 references, 5 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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*Updated 2 November 2026*