UWB at SemEval-2018 Task 3: Irony detection in English tweets

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Abstract

This paper describes our system created for the SemEval-2018 Task 3: Irony detection in English tweets. Our strongly constrained system uses only the provided training data without any additional external resources. Our system is based on Maximum Entropy classifier and various features using parse tree, POS tags, and morphological features. Even without additional lexicons and word embeddings we achieved fourth place in Subtask A and seventh in Subtask B in terms of accuracy.

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APA

Hercig, T. (2018). UWB at SemEval-2018 Task 3: Irony detection in English tweets. In NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop (pp. 520–524). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s18-1084

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