Saudi Arabic Multi-dialects Identification in Social Media Texts

Alahmari, S. orcid.org/0009-0002-6490-3295, Atwell, E. orcid.org/0000-0001-9395-3764 and Alsalka, M.A. orcid.org/0000-0003-3335-1918 (2024) Saudi Arabic Multi-dialects Identification in Social Media Texts. In: Intelligent Computing: Proceedings of the 2024 Computing Conference, Volume 1. Computing Conference 2024 (SAI 2024), 11-12 Jul 2024, London, UK. Lecture Notes in Networks and Systems, 1016. Springer Nature, Cham, Switzerland, pp. 209-217. ISBN: 9783031622809. ISSN: 2367-3370. EISSN: 2367-3389.

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Item Type: Proceedings Paper
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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-62281-6_15.

Keywords: ChatGPT; Saudi Arabic dialects; Dialects identification; Arabic NLP; Social media
Dates:
  • Published (online): 13 June 2024
  • Published: 18 June 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds)
Date Deposited: 26 Nov 2025 09:51
Last Modified: 26 Nov 2025 10:34
Published Version: https://link.springer.com/chapter/10.1007/978-3-03...
Status: Published
Publisher: Springer Nature
Series Name: Lecture Notes in Networks and Systems
Identification Number: 10.1007/978-3-031-62281-6_15
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