KLUEnicorn at SemEval-2018 Task 3: A Naive Approach to Irony Detection

Luise Dürlich


Abstract
This paper describes the KLUEnicorn system submitted to the SemEval-2018 task on “Irony detection in English tweets”. The proposed system uses a naive Bayes classifier to exploit rather simple lexical, pragmatical and semantical features as well as sentiment. It further takes a closer look at different adverb categories and named entities and factors in word-embedding information.
Anthology ID:
S18-1099
Volume:
Proceedings of the 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
607–612
Language:
URL:
https://aclanthology.org/S18-1099
DOI:
10.18653/v1/S18-1099
Bibkey:
Cite (ACL):
Luise Dürlich. 2018. KLUEnicorn at SemEval-2018 Task 3: A Naive Approach to Irony Detection. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 607–612, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
KLUEnicorn at SemEval-2018 Task 3: A Naive Approach to Irony Detection (Dürlich, SemEval 2018)
Copy Citation:
PDF:
https://aclanthology.org/S18-1099.pdf