| | --- |
| | dataset_info: |
| | features: |
| | - name: sentence |
| | dtype: string |
| | - name: label |
| | dtype: int64 |
| | - name: __index_level_0__ |
| | dtype: int64 |
| | splits: |
| | - name: train |
| | num_bytes: 1017693 |
| | num_examples: 13669 |
| | - name: test |
| | num_bytes: 269633 |
| | num_examples: 3400 |
| | download_size: 713636 |
| | dataset_size: 1287326 |
| | configs: |
| | - config_name: default |
| | data_files: |
| | - split: train |
| | path: data/train-* |
| | - split: test |
| | path: data/test-* |
| | license: lgpl-3.0 |
| | task_categories: |
| | - text-classification |
| | language: |
| | - ar |
| | tags: |
| | - arabic |
| | - tunisian |
| | - sentiment_analysis |
| | pretty_name: Tunisian Sentiment Analysis Corpus (TSAC) |
| | size_categories: |
| | - 10K<n<100K |
| | --- |
| | |
| | # Tunisian Sentiment Analysis Corpus (TSAC) |
| |
|
| | The **Tunisian Sentiment Analysis Corpus (TSAC)** is a collection of approximately **17,000 Tunisian Arabic user comments** manually annotated for **sentiment polarity** (positive or negative). |
| | It was collected from Facebook comments written on the official pages of Tunisian radio and TV stations between **January 2015 and June 2016**. |
| |
|
| | This cleaned and Hugging Face–ready version of TSAC provides train/test splits in a simple format compatible with any modern NLP framework. |
| |
|
| | --- |
| |
|
| | ## Dataset Details |
| |
|
| | ### Dataset Description |
| |
|
| | - **Name:** Tunisian Sentiment Analysis Corpus (TSAC) |
| | - **Curated by:** Salima Medhaffar, Fethi Bougares, Yannick Estève, and Lamia Hadrich-Belguith |
| | - **Language:** Tunisian Arabic (Arabic script) |
| | - **License:** Apache License 2.0 |
| | - **Original Repository:** [https://github.com/fbougares/TSAC](https://github.com/fbougares/TSAC) |
| | - **Hugging Face Maintainer:** [tunis-ai](https://huggingface.co/tunis-ai) |
| |
|
| | ### Dataset Sources |
| |
|
| | - **Data collected from:** Official Facebook pages of |
| | - Mosaique FM |
| | - Jawhara FM |
| | - Shems FM |
| | - Hiwar Ettounsi TV |
| | - Nessma TV |
| | - **Timeframe:** January 2015 – June 2016 |
| | - **Paper:** [Medhaffar et al., 2017 — *Sentiment Analysis of Tunisian Dialects: Linguistic Resources and Experiments*](https://aclanthology.org/W17-1307/) |
| |
|
| | --- |
| |
|
| | ## Uses |
| |
|
| | ### Direct Use |
| |
|
| | The dataset is suitable for: |
| | - Sentiment analysis in Tunisian Arabic |
| | - Dialectal Arabic language modeling |
| | - Evaluation of cross-dialectal or multilingual sentiment models |
| |
|
| | ### Out-of-Scope Use |
| |
|
| | - Not suitable for general Modern Standard Arabic (MSA) tasks. |
| | - Not recommended for topic classification or sarcasm detection without adaptation. |
| |
|
| | --- |
| |
|
| | ## Dataset Structure |
| |
|
| | ### Data Fields |
| |
|
| | | Field | Type | Description | |
| | |-------|------|-------------| |
| | | `sentence` | string | User comment written in Tunisian Arabic | |
| | | `label` | int | Sentiment label (1 = positive, 0 = negative) | |
| |
|
| | ### Splits |
| |
|
| | | Split | # Examples | |
| | |--------|-------------| |
| | | Train | 13,669 | |
| | | Test | 3,400 | |
| |
|
| | Splits were created using a stratified partition to maintain class balance. |
| |
|
| | --- |
| |
|
| | ## Dataset Creation |
| |
|
| | ### Curation Rationale |
| |
|
| | The dataset was built to support research in sentiment analysis for **Tunisian Arabic**, a dialect that differs significantly from Modern Standard Arabic and lacks large-scale annotated resources. |
| |
|
| | ### Data Collection and Processing |
| |
|
| | Comments were collected from Facebook public pages using web scraping tools, manually filtered for relevance, and annotated by native Tunisian speakers into two polarity classes: **positive** and **negative**. |
| |
|
| | Preprocessing steps include: |
| | - Removing URLs, emojis, and metadata |
| | - Normalizing Arabic characters |
| | - Deduplicating sentences |
| |
|
| | ### Source Data Producers |
| |
|
| | Public Facebook users posting on the mentioned Tunisian media pages between 2015 and 2016. |
| |
|
| | ### Annotations |
| |
|
| | - **Annotation Type:** Binary sentiment classification (positive/negative) |
| | - **Annotators:** Native Tunisian Arabic speakers |
| | - **Validation:** Manual cross-checking and agreement verification by linguists |
| |
|
| | ### Personal and Sensitive Information |
| |
|
| | Comments are publicly available and were anonymized by removing any identifiable information (e.g., usernames, mentions). |
| |
|
| | --- |
| |
|
| | ## Bias, Risks, and Limitations |
| |
|
| | The dataset reflects opinions expressed on public Facebook pages and may include demographic, temporal, or topical biases. |
| | It should not be used to infer general population sentiment or to train systems that make sensitive decisions about individuals. |
| |
|
| | --- |
| |
|
| | ## Citation |
| |
|
| | If you use this dataset, please cite the following paper: |
| |
|
| | **BibTeX:** |
| | ```bibtex |
| | @inproceedings{medhaffar-etal-2017-sentiment, |
| | title = "Sentiment Analysis of {T}unisian Dialects: Linguistic Resources and Experiments", |
| | author = "Medhaffar, Salima and Bougares, Fethi and Estève, Yannick and Hadrich-Belguith, Lamia", |
| | booktitle = "Proceedings of the Third Arabic Natural Language Processing Workshop", |
| | month = apr, |
| | year = "2017", |
| | address = "Valencia, Spain", |
| | publisher = "Association for Computational Linguistics", |
| | url = "https://aclanthology.org/W17-1307/", |
| | pages = "55--61", |
| | doi = "10.18653/v1/W17-1307" |
| | } |
