PhD Degree Awarded to Ms. Alaa Abdulkarim Hameed Braihi in Computer Science
Ms. Alaa Abdulkarim Hameed Braihi was awarded a PhD degree in Computer Science for her dissertation titled: A Hybrid Approach to Sentiment Analysis of the Yemeni Dialect on Social Media Networks, which was submitted to the Department of Computer Science, Faculty of Computer Science and Information Technology – Sana’a University. The dissertation defense was held on Monday, December 29, 2025.
The PhD Viva-Voce Committee, which was formed based on a resolution issued by the Graduate Studies and Scientific Research Council, consisted of the following:
| # | Committee Members | Designation | Position |
| 1 | Assoc. Prof. Ahmed Abdullah Saleh Al-Shalabi | Internal Examiner | Chair |
| 2 | Assoc. Prof. Mousa Maslah Ahmed Ghurab | Main Supervisor | Member |
| 3 | Assoc. Prof. Fouad Hassan Abdulrazzaq | External Examiner | Member |
The study aimed to.
- Design and evaluate a hybrid sentiment analysis model for the Yemeni dialect, integrating advanced deep learning models with a stacked approach, and leveraging deep neural networks to extract hierarchical features.
- Develop a new sentiment lexicon for the Yemeni dialect, classifying words and expressions according to their polarity and distinguishing between positive and negative terms.
The study introduced a manually annotated Yemeni dialect sentiment dataset consisting of 45,862 Facebook comments, collected from the official pages of major Yemeni telecommunications companies (Yemen Telecom, Yemen Mobile, YOU, and Sabafon). The dataset reflects users’ opinions regarding the services provided by these companies.
The study demonstrated that the proposed model achieved the highest accuracy in Yemeni dialect sentiment analysis. Moreover, it provided a foundational reference, published lexicon, and annotated dataset that can be utilized across various sentiment analysis methodologies related to the Yemeni dialect.
Based on the findings, the researcher recommended:
- Developing a stemming algorithm specifically tailored to the Yemeni dialect
- Expanding and enhancing the Yemeni dialect sentiment lexicon and datasets to cover regional variations
- Addressing potential biases within sentiment analysis resources and models
The dissertation defense was attended by a number of academics, researchers, and specialists, students, colleagues, and the researcher’s family.
