Sina at FigNews 2024: Multilingual Datasets Annotated with Bias and Propaganda

TL;DR

This paper introduces a multilingual, annotated Facebook post dataset focusing on bias and propaganda related to the Israeli War on Gaza, aiding automatic detection efforts with high-quality annotations across five languages.

Contribution

It provides a large, multilingual, fully annotated corpus for bias and propaganda detection, created for the FigNews 2024 Shared Task, with high inter-annotator agreement and open access.

Findings

High inter-annotator agreement (80.8% bias, 70.15% propaganda)

Team ranked among top performers in the shared task

Dataset covers five languages and recent conflict events

Abstract

The proliferation of bias and propaganda on social media is an increasingly significant concern, leading to the development of techniques for automatic detection. This article presents a multilingual corpus of 12, 000 Facebook posts fully annotated for bias and propaganda. The corpus was created as part of the FigNews 2024 Shared Task on News Media Narratives for framing the Israeli War on Gaza. It covers various events during the War from October 7, 2023 to January 31, 2024. The corpus comprises 12, 000 posts in five languages (Arabic, Hebrew, English, French, and Hindi), with 2, 400 posts for each language. The annotation process involved 10 graduate students specializing in Law. The Inter-Annotator Agreement (IAA) was used to evaluate the annotations of the corpus, with an average IAA of 80.8% for bias and 70.15% for propaganda annotations. Our team was ranked among the bestperforming teams in both Bias and Propaganda subtasks. The corpus is open-source and available at https://sina.birzeit.edu/fada