The FIGNEWS Shared Task on News Media Narratives
<|reference_start|>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.<|reference_end|>
@article{zaghouani2024the,
    title={The FIGNEWS Shared Task on News Media Narratives},
    author={Wajdi Zaghouani (1), Mustafa Jarrar (2), Nizar Habash (3), Houda
  Bouamor (4), Imed Zitouni (5), Mona Diab (6), Samhaa R. El-Beltagy (7) and
  Muhammed AbuOdeh (3) ((1) Northwestern University in Qatar, (2) Birzeit
  University, (3) New York University Abu Dhabi, (4) Carnegie Mellon University
  Qatar, (5) Google, (6) Carnegie Mellon University, (7) Newgiza University)},
    journal={arXiv preprint arXiv:2407.18147},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.18147},
    primaryClass={cs.CL}
}