1. Abdul-Mageed, M., & Diab, M. T. (2012). AWATIF: A Multi-Genre Corpus for Modern Standard Arabic Subjectivity and Sentiment Analysis. International Conference on Language Resources and Evaluation. https://api.semanticscholar.org/CorpusID:11657346.
2. Abdul-Mageed, M., & Diab, M. T. (2014). SANA: A Large Scale Multi-Genre, Multi-Dialect Lexicon for Arabic Subjectivity and Sentiment Analysis. International Conference on Language Resources and Evaluation. https://api.semanticscholar.org/CorpusID:10467454.
3. Abdul-Mageed, M., Diab, M., & Kübler, S. (2014). SAMAR: Subjectivity and sentiment analysis for Arabic social media. Computer Speech & Language, 28(1), 20–37. https://doi.org/10.1016/j.csl.2013.03.001.
4. Abo, M. E. M., Shah, N. A. K., Balakrishnan, V., Kamal, M., Abdelaziz, A., & Haruna, K. (2019). SSA-SDA: Subjectivity and sentiment analysis of Sudanese Dialect Arabic. 2019 International Conference on Computer and Information Sciences (ICCIS), 1–5. https://doi.org/10.1109/ICCISci.2019.8716466.
5. Afzal, Z., Pons, E., Kang, N., Sturkenboom, M. C., Schuemie, M. J., & Kors, J. A. (2014). ContextD: An algorithm to identify contextual properties of medical terms in a Dutch clinical corpus. Bmc Bioinformatics, 15(1), 373. https://doi.org/10.1186/s12859-014-0373-3.