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--- |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: test |
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path: data/test-* |
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dataset_info: |
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features: |
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- name: text |
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dtype: string |
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- name: stance |
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dtype: string |
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- name: topic |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 3110594 |
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num_examples: 11500 |
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- name: test |
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num_bytes: 818725 |
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num_examples: 2977 |
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download_size: 1724792 |
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dataset_size: 3929319 |
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task_categories: |
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- text-classification |
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- zero-shot-classification |
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- feature-extraction |
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language: |
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- ar |
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tags: |
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- BERT |
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- MARBERT |
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- Scocial-Media |
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size_categories: |
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- 10K<n<100K |
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--- |
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# ArabicStanceX |
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ArabicStanceX: A large-scale social media dataset for Arabic stance detection (14.5K tweets, 17 topics) |
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ArabicStanceX is a large-scale, richly annotated dataset for stance detection in Arabic social media text. It consists of 14,477 tweets covering 17 diverse topics across six domains: Sport, Education, Health, Religion, Economy, and Other. |
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Dataset Structure |
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The dataset is organized into two main splits: |
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train |
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test |
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Each of these splits contains six topics, one for each domain: |
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education |
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sport |
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health |
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religion |
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economy |
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other |
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Within each domain folder, there are topic-specific .json files. |
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Each .json file corresponds to a specific topic and contains a list of entries. Each entry includes: |
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text: The Arabic tweet content |
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stance: The annotated stance label (favor, against, or none) |
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Citation |
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If you use this dataset in your research, please cite our paper: |
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This dataset is licensed under CC BY 4.0. You are free to share and adapt it with proper attribution. |
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# Citation |
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Alkhathlan, A., Alahmadi, F., Kateb, F., & Al-Khalifa, H. (2025). Constructing and evaluating ArabicStanceX: A social media dataset for Arabic stance detection. Frontiers in Artificial Intelligence, 8, Article 1615800 |
