Bensalem, Imene; Grubišić, Ivan; El Goual, Abdelmoumen; Rosso, Paolo; Charfi, Anis; Zaghouani, Wajdi (2025) Stance Detection in Arabic Dialects: Preliminary Experiments. In: Li, Gang; Filipe, Joaquim; Xu, Zhiwei, (eds.) Arabic Language Processing: From Theory to Practice - 8th International Conference (ICALP 2024) Proceedings Part I. Cham, Switzerland, Springer, pp. 139-150 .
Abstract
Stance detection is a classification task that determines whether a text is in favour, against or neutral towards a particular target. Arabic stance detection remains under-explored. This paper describes our work, which consists in evaluating a new dataset composed of user-generated texts in dialectal and formal Arabic on three targets: general labour union, illegal immigration, and administrative capital. We carried out experiments employing AraBERT-Twitter and Qarib transformers in addition to several machine learning classification models trained using different settings including target-specific and dialect-specific. The results show that training a model for each target, using Qarib, yields the best performance.
| Item Type: | Conference or workshop item published in conference proceedings (UNSPECIFIED) |
|---|---|
| Uncontrolled Keywords: | Stance detection; Arabic dialects; Cross-target stance detection |
| Subjects: | TECHNICAL SCIENCES > Computing > Artificial Intelligence |
| Divisions: | Division of Electronics |
| Depositing User: | Ivan Grubišić |
| Date Deposited: | 15 Jan 2026 11:19 |
| URI: | http://fulir.irb.hr/id/eprint/10853 |
| DOI: | 10.1007/978-3-031-79164-2_12 |
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