ArabDiscrim: A Decade-Long Arabic Facebook Corpus on Racism and Discrimination
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Computer Science > Computation and Language
Title:ArabDiscrim: A Decade-Long Arabic Facebook Corpus on Racism and Discrimination
Abstract:We present ArabDiscrim, a decade-long lexical resource and corpus of 293K public Arabic Facebook posts (2014--2024) discussing racism and discrimination. Unlike existing Twitter-centric datasets, ArabDiscrim integrates platform-native engagement signals, including reactions, shares, comments, and page metadata, enabling joint analysis of language and audience response. The resource includes 200 curated terms (100 racism-related and 100 discrimination-related) with morphological regex families (13+ inflections per lemma), and 20 discrimination axes capturing identity-based grounds for unequal treatment. It also provides explicit attribution patterns. Released under a restricted research-use license for ethical compliance with platform terms, ArabDiscrim supports weak supervision, axis-aware sampling, and platform ecology research. By bridging lexical depth and ecological validity, it establishes a foundation for fairness-oriented, platform-aware Arabic NLP.
| Comments: | Accepted at LREC 2026 Main Conference |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2605.22081 [cs.CL] |
| (or arXiv:2605.22081v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2605.22081
arXiv-issued DOI via DataCite (pending registration)
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