Abstract
This paper details our participation in the FIGNEWS-2024 shared task on bias and propaganda annotation in Gaza conflict news. Our objectives were to develop robust guidelines and annotate a substantial dataset to enhance bias detection. We iteratively refined our guidelines and used examples for clarity. Key findings include the challenges in achieving high inter-annotator agreement and the importance of annotator awareness of their own biases. We also explored the integration of ChatGPT as an annotator to support consistency. This paper contributes to the field by providing detailed annotation guidelines, and offering insights into the subjectivity of bias annotation.- Anthology ID:
- 2024.arabicnlp-1.62
- Volume:
- Proceedings of The Second Arabic Natural Language Processing Conference
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Nizar Habash, Houda Bouamor, Ramy Eskander, Nadi Tomeh, Ibrahim Abu Farha, Ahmed Abdelali, Samia Touileb, Injy Hamed, Yaser Onaizan, Bashar Alhafni, Wissam Antoun, Salam Khalifa, Hatem Haddad, Imed Zitouni, Badr AlKhamissi, Rawan Almatham, Khalil Mrini
- Venues:
- ArabicNLP | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 580–589
- Language:
- URL:
- https://aclanthology.org/2024.arabicnlp-1.62
- DOI:
- Cite (ACL):
- Jasmin Heierli, Silvia Pareti, Serena Pareti, and Tatiana Lando. 2024. Bias Bluff Busters at FIGNEWS 2024 Shared Task: Developing Guidelines to Make Bias Conscious. In Proceedings of The Second Arabic Natural Language Processing Conference, pages 580–589, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- Bias Bluff Busters at FIGNEWS 2024 Shared Task: Developing Guidelines to Make Bias Conscious (Heierli et al., ArabicNLP-WS 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.arabicnlp-1.62.pdf