@inproceedings{dearden-baron-2018-lancaster,
title = "{L}ancaster at {S}em{E}val-2018 Task 3: Investigating Ironic Features in {E}nglish Tweets",
author = "Dearden, Edward and
Baron, Alistair",
booktitle = "Proceedings of The 12th International Workshop on Semantic Evaluation",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S18-1096",
doi = "10.18653/v1/S18-1096",
pages = "587--593",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Lancaster at SemEval-2018 Task 3: Investigating Ironic Features in English Tweets
%A Dearden, Edward
%A Baron, Alistair
%S Proceedings of The 12th International Workshop on Semantic Evaluation
%D 2018
%8 jun
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F dearden-baron-2018-lancaster
%X 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.
%R 10.18653/v1/S18-1096
%U https://aclanthology.org/S18-1096
%U https://doi.org/10.18653/v1/S18-1096
%P 587-593
Markdown (Informal)
[Lancaster at SemEval-2018 Task 3: Investigating Ironic Features in English Tweets](https://aclanthology.org/S18-1096) (Dearden & Baron, SemEval 2018)
ACL