%0 Conference Proceedings %T ECNU at SemEval-2018 Task 3: Exploration on Irony Detection from Tweets via Machine Learning and Deep Learning Methods %A Yin, Zhenghang %A Wang, Feixiang %A Lan, Man %A Wang, Wenting %Y Apidianaki, Marianna %Y Mohammad, Saif M. %Y May, Jonathan %Y Shutova, Ekaterina %Y Bethard, Steven %Y Carpuat, Marine %S Proceedings of the 12th International Workshop on Semantic Evaluation %D 2018 %8 June %I Association for Computational Linguistics %C New Orleans, Louisiana %F yin-etal-2018-ecnu %X 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. %R 10.18653/v1/S18-1098 %U https://aclanthology.org/S18-1098 %U https://doi.org/10.18653/v1/S18-1098 %P 600-606