The FIGNEWS Shared Task on News Media Narratives
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.
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Wajdi Zaghouani
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Mustafa Jarrar
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2024-07-26T21:16:14.762Z
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Mustafa Jarrar
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mjarrar
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Nizar Habash
extracted_confirmed
2024-08-05T07:19:27.508Z
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Nizar Habash
user
nizarhabash
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Houda Bouamor
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Imed Zitouni
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Mona Diab
66a4121d9ba24c304046322b
Samhaa R. El-Beltagy
66a4121d9ba24c304046322c
Muhammed AbuOdeh
The FIGNEWS Shared Task on News Media Narratives
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.