Abstract
The paper describes our submissions to task 3 in SemEval-2018. There are two subtasks: Subtask A is a binary classification task to determine whether a tweet is ironic, and Subtask B is a fine-grained classification task including four classes. To address them, we explored supervised machine learning method alone and in combination with neural networks.- Anthology ID:
- S18-1098
- Volume:
- Proceedings of the 12th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Venues:
- SemEval | *SEM
- SIGs:
- SIGLEX | SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 600–606
- Language:
- URL:
- https://aclanthology.org/S18-1098
- DOI:
- 10.18653/v1/S18-1098
- Cite (ACL):
- Zhenghang Yin, Feixiang Wang, Man Lan, and Wenting Wang. 2018. ECNU at SemEval-2018 Task 3: Exploration on Irony Detection from Tweets via Machine Learning and Deep Learning Methods. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 600–606, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- ECNU at SemEval-2018 Task 3: Exploration on Irony Detection from Tweets via Machine Learning and Deep Learning Methods (Yin et al., SemEval-*SEM 2018)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/S18-1098.pdf