This project focuses on developing advanced models for diverse text classification tasks, including sentiment analysis, hate speech detection, and sarcasm detection.
This project is funded by:
- Jinho Choi - Associate Professor at Emory University
- XD at SemEval-2020 Task 12: Ensemble Approach to Offensive Language Identification in Social Media Using Transformer Encoders. Dong, X.; and Choi, J. D. Proceedings of the International Workshop on Semantic Evaluation 2020 Task 12: OffensEval 2: Multilingual Offensive Language Identification in Social Media (SemEval), 2020.
- Transformer-based Context-aware Sarcasm Detection in Conversation Threads from Social Media. Dong, X.; Li, C.; and Choi, J. D. Proceedings of the ACL Workshop on Figurative Language Processing: Shared Task on Sarcasm Detection (FigLang:ST), 2020.
- Event Analysis on the 2016 U.S. Presidential Election Using Social Media. Shaban, T.; Hexter, L.; and Choi, J. D. Proceedings of the International Conference on Social Informatics (SocInfo), Oxford, UK, 2017.
- Lexicon Integrated CNN Models with Attention for Sentiment Analysis. Shin, B.; Lee, T.; and Choi, J. D. In Proceedings of the EMNLP Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA), 2017.
- Improving Document Clustering by Eliminating Unnatural Language. Jang, M.; Choi, J. D.; and Allan, J. Proceedings of the EMNLP Workshop on Noisy User-generated Text (WNUT), 2017.
- Computational Exploration of the Linguistic Structures of Future-Oriented Expression: Classification and Categorization. Nie, A.; Shepard, J.; Choi, J. D.; Copley, B.; and Wolff, P. Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop (NAACL:SRW), 2015.