@inproceedings{durlich-2018-kluenicorn,
title = "{KLUE}nicorn at {S}em{E}val-2018 Task 3: A Naive Approach to Irony Detection",
author = {D{\"u}rlich, Luise},
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/S18-1099",
doi = "10.18653/v1/S18-1099",
pages = "607--612",
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.",
}
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%0 Conference Proceedings
%T KLUEnicorn at SemEval-2018 Task 3: A Naive Approach to Irony Detection
%A Dürlich, Luise
%S Proceedings of The 12th International Workshop on Semantic Evaluation
%D 2018
%8 jun
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F durlich-2018-kluenicorn
%X 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.
%R 10.18653/v1/S18-1099
%U https://aclanthology.org/S18-1099
%U https://doi.org/10.18653/v1/S18-1099
%P 607-612
Markdown (Informal)
[KLUEnicorn at SemEval-2018 Task 3: A Naive Approach to Irony Detection](https://aclanthology.org/S18-1099) (Dürlich, SemEval 2018)
ACL