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.

[img]
Preview
PDF (dearden-semeval2018)
dearden_semeval2018.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.

Download (107kB)

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
ID Code:
125778
Deposited By:
Deposited On:
12 Jun 2018 13:36
Refereed?:
Yes
Published?:
Published
Last Modified:
19 Sep 2020 07:07