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New corpus targets fake news in North African languages

Researchers have developed BOUTEF, a new multilingual corpus aimed at studying fake news in North Africa, specifically Algeria and Tunisia. This dataset includes fake and genuine narratives, user comments, and debunking information across various languages and dialects, including Arabic dialects, French, and English. The analysis reveals that fake news often uses emotionally charged language and sensational framing to increase virality, while debunking content is more factual. The corpus is intended to advance research in fake news detection and low-resource language processing. AI

IMPACT Provides a valuable resource for developing and testing AI models for fake news detection in under-resourced multilingual contexts.

RANK_REASON The cluster contains an academic paper introducing a new dataset for research purposes. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Kamel Smaili, Yassine Toughrai, Amina Laggoun, David Langlois ·

    BOUTEF: A Multilingual Corpus for FakeNews in North Africa -- Language as a Weapon

    arXiv:2606.00193v1 Announce Type: new Abstract: The rapid spread of fake news on social media has become a major challenge, particularly in multilingual and under-resourced contexts such as North Africa. In this paper, we introduce BOUTEF, a large-scale multilingual corpus design…