An End-to-End Hybrid Framework for Rumour Detection in Low-Resources Algerian Dialect

arXiv:2606.13411v1 Announce Type: new Abstract: The rapid growth of social media has intensified the spread of rumours. This issue is more challenging in the Algerian context due to the informal and code-switched nature of dialectal content, the scarcity of annotated resources, and the limited effectiveness of standard Arabic NLP tools on dialect text. This paper presents an end-to-end rumour detection hybrid framework for Algerian dialect social media content. We build a domain-specific annotated dataset by combining real social media posts, synthetic data, and the FASSILA corpus, with automa

Source: arXiv cs.CL — read the full report at the original publisher.

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