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.

翻译：本文介绍了FIGNEWS共享任务的概况，该任务作为与ACL 2024联合举办的ArabicNLP 2024会议的一部分而组织。该共享任务致力于多语言新闻帖文中的偏见与宣传内容标注研究，并以以色列-加沙战争初期作为案例进行重点分析。任务旨在通过构建分析多元叙事框架以识别潜在偏见与宣传内容，从而推动主观性任务标注规范制定的协作研究。为促进与鼓励多样性，我们从多语言视角切入该问题，具体涵盖英语、法语、阿拉伯语、希伯来语和印地语五种语言。共有17支团队参与了两个标注子任务：偏见标注（16支团队）和宣传标注（6支团队）。各团队在四个评估维度展开角逐：标注规范制定、标注质量、标注数量及标注一致性。所有团队累计产生了129,800个数据点。本文最后讨论了该领域的关键发现与启示。