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  3. **transcripts/**: A folder containing the text transcripts of the audio files.
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  4. **annotations.csv**: A CSV file that includes the annotations for each record, detailing sentiment labels, sarcasm markers, and other relevant metadata.
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  ### License
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  The AR-MUSA dataset is licensed under the Academic Free License 3.0 (afl-3.0) and is provided for research purposes only. Any use of this dataset must comply with the terms of this license.
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  ### Citation
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- If you use the AR-MUSA dataset in your research, please cite the following paper:
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  @article{khaled2025ar,
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  title={AR-MUSA: a multimodal benchmark dataset and evaluation framework for Arabic sentiment analysis},
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  author={Khaled, S. and Ragab, M. E. and Helmy, A. K. and Medhat, W. and Mohamed, E. H.},
@@ -67,4 +79,4 @@ If you use the AR-MUSA dataset in your research, please cite the following paper
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  pages={30-44},
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  year={2025},
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  doi={10.22266/ijies2025.0531.03}
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- }
 
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  3. **transcripts/**: A folder containing the text transcripts of the audio files.
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  4. **annotations.csv**: A CSV file that includes the annotations for each record, detailing sentiment labels, sarcasm markers, and other relevant metadata.
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+
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  ### License
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  The AR-MUSA dataset is licensed under the Academic Free License 3.0 (afl-3.0) and is provided for research purposes only. Any use of this dataset must comply with the terms of this license.
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+ ### Research Paper
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+
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+ For detailed information on the dataset construction, validation procedures, and experimental results, please refer to our published paper:
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+ **Khaled, S., Ragab, M. E., Helmy, A. K., Medhat, W., & Mohamed, E. H.** (2025). *AR-MUSA: A multimodal benchmark dataset and evaluation framework for Arabic sentiment analysis*. **International Journal of Intelligent Engineering and Systems**, 18(4), 30–44.
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+ 🔗 [Read the paper](https://doi.org/10.22266/ijies2025.0531.03)
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+
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+ ---
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+
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  ### Citation
 
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+ If you use the **AR-MUSA** dataset in your research, please cite the following paper:
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+ ```bibtex
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  @article{khaled2025ar,
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  title={AR-MUSA: a multimodal benchmark dataset and evaluation framework for Arabic sentiment analysis},
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  author={Khaled, S. and Ragab, M. E. and Helmy, A. K. and Medhat, W. and Mohamed, E. H.},
 
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  pages={30-44},
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  year={2025},
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  doi={10.22266/ijies2025.0531.03}
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+ }