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--- |
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task_categories: |
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- text-classification |
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language: |
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- ar |
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pretty_name: 'Mawqif: Stance Detection' |
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size_categories: |
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- 1K<n<10K |
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tags: |
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- Stance Detection |
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- Sentiment Analysis |
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- Sarcasm Detection |
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--- |
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# Mawqif: A Multi-label Arabic Dataset for Target-specific Stance Detection |
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- *Mawqif* is the first Arabic dataset that can be used for target-specific stance detection. |
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- This is a multi-label dataset where each data point is annotated for stance, sentiment, and sarcasm. |
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- We benchmark *Mawqif* dataset on the stance detection task and evaluate the performance of four BERT-based models. Our best model achieves a macro-F1 of 78.89\%. |
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# Mawqif Statistics |
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- This dataset consists of 4,121 tweets in multi-dialectal Arabic. Each tweet is annotated with a stance toward one of three targets: “COVID-19 vaccine,” “digital transformation,” and “women empowerment.” In addition, it is annotated with sentiment and sarcasm polarities. |
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- The following figure illustrates the labels’ distribution across all targets, and the distribution per target. |
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<img width="738" alt="dataStat-2" src="https://user-images.githubusercontent.com/31368075/188299057-54d04e87-802d-4b0e-b7c6-56bdc1078284.png"> |
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# Interactive Visualization |
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To browse an interactive visualization of the *Mawqif* dataset, please click [here](https://public.tableau.com/views/MawqifDatasetDashboard/Dashboard1?:language=en-US&publish=yes&:display_count=n&:origin=viz_share_link) |
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- *You can click on visualization components to filter the data by target and by class. **For example,** you can click on “women empowerment" and "against" to get the information of tweets that express against women empowerment.* |
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# Citation |
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If you feel our paper and resources are useful, please consider citing our work! |
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``` |
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@inproceedings{alturayeif-etal-2022-mawqif, |
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title = "Mawqif: A Multi-label {A}rabic Dataset for Target-specific Stance Detection", |
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author = "Alturayeif, Nora Saleh and |
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Luqman, Hamzah Abdullah and |
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Ahmed, Moataz Aly Kamaleldin", |
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booktitle = "Proceedings of the The Seventh Arabic Natural Language Processing Workshop (WANLP)", |
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month = dec, |
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year = "2022", |
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address = "Abu Dhabi, United Arab Emirates (Hybrid)", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2022.wanlp-1.16", |
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pages = "174--184" |
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} |
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``` |
