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Lancaster at SemEval-2018 Task 3: Investigating Ironic Features in English Tweets

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

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Lancaster at SemEval-2018 Task 3 : Investigating Ironic Features in English Tweets. / Dearden, Edward; Baron, Alistair.

Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval-2018). Association for Computational Linguistics, 2018. p. 587-593.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

Harvard

Dearden, E & Baron, A 2018, Lancaster at SemEval-2018 Task 3: Investigating Ironic Features in English Tweets. in Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval-2018). Association for Computational Linguistics, pp. 587-593.

APA

Dearden, E., & Baron, A. (2018). Lancaster at SemEval-2018 Task 3: Investigating Ironic Features in English Tweets. In Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval-2018) (pp. 587-593). Association for Computational Linguistics.

Vancouver

Dearden E, Baron A. Lancaster at SemEval-2018 Task 3: Investigating Ironic Features in English Tweets. In Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval-2018). Association for Computational Linguistics. 2018. p. 587-593

Author

Dearden, Edward ; Baron, Alistair. / Lancaster at SemEval-2018 Task 3 : Investigating Ironic Features in English Tweets. Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval-2018). Association for Computational Linguistics, 2018. pp. 587-593

Bibtex

@inproceedings{189ace884b714f91a63c66a5579cfeb8,
title = "Lancaster at SemEval-2018 Task 3: Investigating Ironic Features in English Tweets",
abstract = "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.",
author = "Edward Dearden and Alistair Baron",
year = "2018",
month = jun
day = "6",
language = "English",
pages = "587--593",
booktitle = "Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval-2018)",
publisher = "Association for Computational Linguistics",

}

RIS

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 -