الأبحاث المنشورة

• Abdullah I. Alharbi & Mark Lee. (2020). Combining Character and Word Embeddings for the Detection of Offensive Language in Arabic. In Proceedings of the 4th Workshop on Open-Source Arabic Corpora and Processing Tools, with a Shared Task on Offensive Language Detection (pp. 91-96). (Paper Link)
  
• Abdullah I. Alharbi & Mark Lee. (2020). Combining Character and Word Embeddings for Affect in Arabic Informal Social Media Microblogs. In International Conference on Applications of Natural Language to Information Systems (pp. 213-224). Springer, Cham. [Best Paper Award] (Paper Link)
  
• Abdullah I. Alharbi & Mark Lee. (2020). BhamNLP at SemEval-2020 Task 12: An Ensemble of Different Word Embeddings and Emotion Transfer Learning for Arabic Offensive Language Identification in Social Media. In the International Workshop on Semantic Evaluation (SemEval2020). (Paper Link)
  
• Abdullah I. Alharbi & Mark Lee. (2021). Multi-task Learning Using a Combination of Contextualised and Static Word Embeddings for Arabic Sarcasm Detection and Sentiment Analysis . In EACL | WANLP [Winning System Award] (Paper Link)
  
• Abdullah I. Alharbi, Phillip Smith & Mark Lee. (2021). Enhancing Contextualised Language Models with Static Character and Word Embeddings for Emotional Intensity and Sentiment Strength Detection in Arabic Tweets. In the 5th International Conference on AI in Computational Linguistics (ACLing 2021). (Paper Link)
• Abdullah I. Alharbi, Phillip Smith & Mark Lee. (2022). Integrating Character-level and Word-level Representation for Affect in Arabic Tweets. Data & Knowledge Engineering, 138, 101973.. (Paper Link)