WLV at SemEval-2018 Task 3: Dissecting Tweets in Search of Irony

Omid Rohanian, Shiva Taslimipoor, Richard Evans, Ruslan Mitkov


Abstract
This paper describes the systems submitted to SemEval 2018 Task 3 “Irony detection in English tweets” for both subtasks A and B. The first system leveraging a combination of sentiment, distributional semantic, and text surface features is ranked third among 44 teams according to the official leaderboard of the subtask A. The second system with slightly different representation of the features ranked ninth in subtask B. We present a method that entails decomposing tweets into separate parts. Searching for contrast within the constituents of a tweet is an integral part of our system. We embrace an extensive definition of contrast which leads to a vast coverage in detecting ironic content.
Anthology ID:
S18-1090
Volume:
Proceedings of The 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
553–559
Language:
URL:
https://www.aclweb.org/anthology/S18-1090
DOI:
10.18653/v1/S18-1090
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1090.pdf