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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
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TY - GEN
T1 - Lancaster at SemEval-2018 Task 3
T2 - Investigating Ironic Features in English Tweets
AU - Dearden, Edward
AU - Baron, Alistair
PY - 2018/6/6
Y1 - 2018/6/6
N2 - This paper describes the system we submitted to SemEval-2018 Task 3. The aim of the system is to distinguish between irony and non-irony in English tweets. We create a targeted feature set and analyse how different features are useful in the task of irony detection, achieving an F1-score of 0.5914. The analysis of individual features provides insight that may be useful in future attempts at detecting irony in tweets.
AB - This paper describes the system we submitted to SemEval-2018 Task 3. The aim of the system is to distinguish between irony and non-irony in English tweets. We create a targeted feature set and analyse how different features are useful in the task of irony detection, achieving an F1-score of 0.5914. The analysis of individual features provides insight that may be useful in future attempts at detecting irony in tweets.
M3 - Conference contribution/Paper
SP - 587
EP - 593
BT - Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval-2018)
PB - Association for Computational Linguistics
ER -