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Advancing AI-Driven Linguistic Analysis: Developing and Annotating Comprehensive Arabic Dialect Corpora for Gulf Countries and Saudi Arabia

Author

Listed:
  • Nouf Al-Shenaifi

    (Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia)

  • Aqil M. Azmi

    (Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia)

  • Manar Hosny

    (Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia)

Abstract

This study harnesses the linguistic diversity of Arabic dialects to create two expansive corpora from X (formerly Twitter). The Gulf Arabic Corpus (GAC-6) includes around 1.7 million tweets from six Gulf countries—Saudi Arabia, UAE, Qatar, Oman, Kuwait, and Bahrain—capturing a wide range of linguistic variations. The Saudi Dialect Corpus (SDC-5) comprises 790,000 tweets, offering in-depth insights into five major regional dialects of Saudi Arabia: Hijazi, Najdi, Southern, Northern, and Eastern, reflecting the complex linguistic landscape of the region. Both corpora are thoroughly annotated with dialect-specific seed words and geolocation data, achieving high levels of accuracy, as indicated by Cohen’s Kappa scores of 0.78 for GAC-6 and 0.90 for SDC-5. The annotation process leverages AI-driven techniques, including machine learning algorithms for automated dialect recognition and feature extraction, to enhance the granularity and precision of the data. These resources significantly contribute to the field of Arabic dialectology and facilitate the development of AI algorithms for linguistic data analysis, enhancing AI system design and efficiency. The data provided by this research are crucial for advancing AI methodologies, supporting diverse applications in the realm of next-generation AI technologies.

Suggested Citation

  • Nouf Al-Shenaifi & Aqil M. Azmi & Manar Hosny, 2024. "Advancing AI-Driven Linguistic Analysis: Developing and Annotating Comprehensive Arabic Dialect Corpora for Gulf Countries and Saudi Arabia," Mathematics, MDPI, vol. 12(19), pages 1-18, October.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:19:p:3120-:d:1492721
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    References listed on IDEAS

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    1. Al-Razgan, Muna & Alrowily, Asma & Al-Matham, Rawan N. & Alghamdi, Khulood M. & Shaabi, Maha & Alssum, Lama, 2021. "Using diffusion of innovation theory and sentiment analysis to analyze attitudes toward driving adoption by Saudi women," Technology in Society, Elsevier, vol. 65(C).
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