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

Dearden, Edward and Baron, Alistair (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.

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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.

Item Type: Contribution in Book/Report/Proceedings
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 125778
Deposited By: ep_importer_pure
Deposited On: 12 Jun 2018 13:36
Refereed?: Yes
Published?: Published
Last Modified: 22 Feb 2020 05:56
URI: https://eprints.lancs.ac.uk/id/eprint/125778

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