@inproceedings{nikhil-mayank-srivastava-2018-binarizer,
title = "Binarizer at {S}em{E}val-2018 Task 3: Parsing dependency and deep learning for irony detection",
author = "Nikhil, Nishant and
Mayank Srivastava, Muktabh",
editor = "Apidianaki, Marianna and
Mohammad, Saif M. and
May, Jonathan and
Shutova, Ekaterina and
Bethard, Steven and
Carpuat, Marine",
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/S18-1102",
doi = "10.18653/v1/S18-1102",
pages = "628--632",
abstract = "In this paper, we describe the system submitted for the SemEval 2018 Task 3 (Irony detection in English tweets) Subtask A by the team Binarizer. Irony detection is a key task for many natural language processing works. Our method treats ironical tweets to consist of smaller parts containing different emotions. We break down tweets into separate phrases using a dependency parser. We then embed those phrases using an LSTM-based neural network model which is pre-trained to predict emoticons for tweets. Finally, we train a fully-connected network to achieve classification.",
}
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<abstract>In this paper, we describe the system submitted for the SemEval 2018 Task 3 (Irony detection in English tweets) Subtask A by the team Binarizer. Irony detection is a key task for many natural language processing works. Our method treats ironical tweets to consist of smaller parts containing different emotions. We break down tweets into separate phrases using a dependency parser. We then embed those phrases using an LSTM-based neural network model which is pre-trained to predict emoticons for tweets. Finally, we train a fully-connected network to achieve classification.</abstract>
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%0 Conference Proceedings
%T Binarizer at SemEval-2018 Task 3: Parsing dependency and deep learning for irony detection
%A Nikhil, Nishant
%A Mayank Srivastava, Muktabh
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Bethard, Steven
%Y Carpuat, Marine
%S Proceedings of the 12th International Workshop on Semantic Evaluation
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F nikhil-mayank-srivastava-2018-binarizer
%X In this paper, we describe the system submitted for the SemEval 2018 Task 3 (Irony detection in English tweets) Subtask A by the team Binarizer. Irony detection is a key task for many natural language processing works. Our method treats ironical tweets to consist of smaller parts containing different emotions. We break down tweets into separate phrases using a dependency parser. We then embed those phrases using an LSTM-based neural network model which is pre-trained to predict emoticons for tweets. Finally, we train a fully-connected network to achieve classification.
%R 10.18653/v1/S18-1102
%U https://aclanthology.org/S18-1102
%U https://doi.org/10.18653/v1/S18-1102
%P 628-632
Markdown (Informal)
[Binarizer at SemEval-2018 Task 3: Parsing dependency and deep learning for irony detection](https://aclanthology.org/S18-1102) (Nikhil & Mayank Srivastava, SemEval 2018)
ACL