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

Tomáš Hercig


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.
Anthology ID:
S18-1084
Volume:
Proceedings of The 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
520–524
Language:
URL:
https://www.aclweb.org/anthology/S18-1084
DOI:
10.18653/v1/S18-1084
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1084.pdf