Summary of Sina at Fignews 2024: Multilingual Datasets Annotated with Bias and Propaganda, by Lina Duaibes et al.
Sina at FigNews 2024: Multilingual Datasets Annotated with Bias and Propaganda
by Lina Duaibes, Areej Jaber, Mustafa Jarrar, Ahmad Qadi, Mais Qandeel
First submitted to arxiv on: 12 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents a multilingual corpus of 12,000 Facebook posts annotated for bias and propaganda. The corpus is part of the FigNews 2024 Shared Task on News Media Narratives, which frames the Israeli War on Gaza from October 7, 2023 to January 31, 2024. The corpus includes 2,400 posts in five languages (Arabic, Hebrew, English, French, and Hindi). The annotation process was conducted by 10 graduate students specializing in Law, with an average Inter-Annotator Agreement of 80.8% for bias and 70.15% for propaganda annotations. Our team ranked among the best-performing teams in both Bias and Propaganda subtasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper creates a big database of Facebook posts that are labeled as biased or propagandistic. This helps researchers understand how social media can be used to spread misinformation. The database is special because it’s in many languages, like Arabic, Hebrew, English, French, and Hindi. The people who labeled the posts were law students, and they mostly agreed with each other on what was biased and what wasn’t. |
