iabufarha/ar_sarcasm
Dataset Card for ArSarcasm Dataset Summary ArSarcasm is a new Arabic sarcasm detection dataset. The dataset was created using previously available Arabic sentiment analysis datasets (SemEval 2017 and ASTD) and adds sarcasm and dialect labels to them. The dataset contains 10,547 tweets, 1,682 (16%) of which are sarcastic. For more details, please check the paper From Arabic Sentiment Analysis to Sarcasm Detection: The ArSarcasm Dataset Supported Tasks… See the full description on the dataset page: https://huggingface.co/datasets/iabufarha/ar_sarcasm.
| Author / organization | iabufarha |
|---|---|
| License (as declared) | mit |
| Downloads | 480 (as reported by Hugging Face) |
| Likes | 18 |
| Created | 2 March 2022 |
| Last updated at source | 9 January 2024 |
Popularity, last 2 days
480 now (+11 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- mradermacher/ara-jev-Faisal-GGUFModel · used to train
- IbrahimAmin/marbertv2-arabic-written-dialect-classifierModel · used to train
- Omartificial-Intelligence-Space/ara-jev-FaisalModel · used to train
- Elafnawaf/gliner2-arabic-saudiModel · used to train
Recent changes
- 16 Oct 2026 Description: Dataset Card for ArSarcasm Dataset Summary ArSarcasm is a new Arabic sarcasm detection dataset. The dataset was created using previously available Arabic sentiment analysis datasets (SemEval 2017 and ASTD) and adds sarcasm and dialect label → Dataset Card for ArSarcasm Dataset Summary ArSarcasm is a new Arabic sarcasm detection dataset. The dataset was created using previously available Arabic sentiment analysis datasets (SemEval 2017 and ASTD) and adds sarcasm and dialect label
Changes detected by Silytics between refreshes of the source.
Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.