Saskia Heisterborg


2024

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GroningenAnnotatesGaza at the FIGNEWS 2024 Shared Task: Analyzing Bias in Conflict Narratives
Khalid Khatib | Sara Gemelli | Saskia Heisterborg | Pritha Majumdar | Gosse Minnema | Arianna Muti | Noa Solissa
Proceedings of The Second Arabic Natural Language Processing Conference

In this paper we report the development of our annotation methodology for the shared task FIGNEWS 2024. The objective of the shared task is to look into the layers of bias in how the war on Gaza is represented in media narrative. Our methodology follows the prescriptive paradigm, in which guidelines are detailed and refined through an iterative process in which edge cases are discussed and converged. Our IAA score (Krippendorffā€™s š¯›¼) is 0.420, highlighting the challenging and subjective nature of the task. Our results show that 52% of posts were unbiased, 42% biased against Palestine, 5% biased against Israel, and 3% biased against both. 16% were unclear or not applicable.