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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
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2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.18147 |
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| _version_ | 1866929437181739008 |
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| author | Zaghouani, Wajdi Jarrar, Mustafa Habash, Nizar Bouamor, Houda Zitouni, Imed Diab, Mona El-Beltagy, Samhaa R. AbuOdeh, Muhammed |
| author_facet | Zaghouani, Wajdi Jarrar, Mustafa Habash, Nizar Bouamor, Houda Zitouni, Imed Diab, Mona El-Beltagy, Samhaa R. AbuOdeh, Muhammed |
| contents | We present an overview of the FIGNEWS shared task, organized as part of the ArabicNLP 2024 conference co-located with ACL 2024. The shared task addresses bias and propaganda annotation in multilingual news posts. We focus on the early days of the Israel War on Gaza as a case study. The task aims to foster collaboration in developing annotation guidelines for subjective tasks by creating frameworks for analyzing diverse narratives highlighting potential bias and propaganda. In a spirit of fostering and encouraging diversity, we address the problem from a multilingual perspective, namely within five languages: English, French, Arabic, Hebrew, and Hindi. A total of 17 teams participated in two annotation subtasks: bias (16 teams) and propaganda (6 teams). The teams competed in four evaluation tracks: guidelines development, annotation quality, annotation quantity, and consistency. Collectively, the teams produced 129,800 data points. Key findings and implications for the field are discussed. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_18147 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | The FIGNEWS Shared Task on News Media Narratives Zaghouani, Wajdi Jarrar, Mustafa Habash, Nizar Bouamor, Houda Zitouni, Imed Diab, Mona El-Beltagy, Samhaa R. AbuOdeh, Muhammed Computation and Language We present an overview of the FIGNEWS shared task, organized as part of the ArabicNLP 2024 conference co-located with ACL 2024. The shared task addresses bias and propaganda annotation in multilingual news posts. We focus on the early days of the Israel War on Gaza as a case study. The task aims to foster collaboration in developing annotation guidelines for subjective tasks by creating frameworks for analyzing diverse narratives highlighting potential bias and propaganda. In a spirit of fostering and encouraging diversity, we address the problem from a multilingual perspective, namely within five languages: English, French, Arabic, Hebrew, and Hindi. A total of 17 teams participated in two annotation subtasks: bias (16 teams) and propaganda (6 teams). The teams competed in four evaluation tracks: guidelines development, annotation quality, annotation quantity, and consistency. Collectively, the teams produced 129,800 data points. Key findings and implications for the field are discussed. |
| title | The FIGNEWS Shared Task on News Media Narratives |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2407.18147 |