BSC-LANGTECH at FIGNEWS 2024 Shared Task: Exploring Semi-Automatic Bias Annotation using Frame Analysis

Valle Ruiz-Fernández, José Saiz, Aitor Gonzalez-Agirre


Abstract
This paper introduces the methodology of BSC-LANGTECH team for the FIGNEWS 2024 Shared Task on News Media Narratives. Following the bias annotation subtask, we apply the theory and methods of framing analysis to develop guidelines to annotate bias in the corpus provided by the task organizators. The manual annotation of a subset, with which a moderate IAA agreement has been achieved, is further used in Deep Learning techniques to explore automatic annotation and test the reliability of our framework.
Anthology ID:
2024.arabicnlp-1.67
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:
620–629
Language:
URL:
https://aclanthology.org/2024.arabicnlp-1.67
DOI:
Bibkey:
Cite (ACL):
Valle Ruiz-Fernández, José Saiz, and Aitor Gonzalez-Agirre. 2024. BSC-LANGTECH at FIGNEWS 2024 Shared Task: Exploring Semi-Automatic Bias Annotation using Frame Analysis. In Proceedings of The Second Arabic Natural Language Processing Conference, pages 620–629, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
BSC-LANGTECH at FIGNEWS 2024 Shared Task: Exploring Semi-Automatic Bias Annotation using Frame Analysis (Ruiz-Fernández et al., ArabicNLP-WS 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.arabicnlp-1.67.pdf