@inproceedings{ghanem-etal-2018-ldr,
title = "{LDR} at {S}em{E}val-2018 Task 3: A Low Dimensional Text Representation for Irony Detection",
author = "Ghanem, Bilal and
Rangel, Francisco and
Rosso, Paolo",
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/S18-1086",
doi = "10.18653/v1/S18-1086",
pages = "531--536",
abstract = "In this paper we describe our participation in the SemEval-2018 task 3 Shared Task on Irony Detection. We have approached the task with our low dimensionality representation method (LDR), which exploits low dimensional features extracted from text on the basis of the occurrence probability of the words depending on each class. Our intuition is that words in ironic texts have different probability of occurrence than in non-ironic ones. Our approach obtained acceptable results in both subtasks A and B. We have performed an error analysis that shows the difference on correct and incorrect classified tweets.",
}
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<abstract>In this paper we describe our participation in the SemEval-2018 task 3 Shared Task on Irony Detection. We have approached the task with our low dimensionality representation method (LDR), which exploits low dimensional features extracted from text on the basis of the occurrence probability of the words depending on each class. Our intuition is that words in ironic texts have different probability of occurrence than in non-ironic ones. Our approach obtained acceptable results in both subtasks A and B. We have performed an error analysis that shows the difference on correct and incorrect classified tweets.</abstract>
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%0 Conference Proceedings
%T LDR at SemEval-2018 Task 3: A Low Dimensional Text Representation for Irony Detection
%A Ghanem, Bilal
%A Rangel, Francisco
%A Rosso, Paolo
%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 ghanem-etal-2018-ldr
%X In this paper we describe our participation in the SemEval-2018 task 3 Shared Task on Irony Detection. We have approached the task with our low dimensionality representation method (LDR), which exploits low dimensional features extracted from text on the basis of the occurrence probability of the words depending on each class. Our intuition is that words in ironic texts have different probability of occurrence than in non-ironic ones. Our approach obtained acceptable results in both subtasks A and B. We have performed an error analysis that shows the difference on correct and incorrect classified tweets.
%R 10.18653/v1/S18-1086
%U https://aclanthology.org/S18-1086
%U https://doi.org/10.18653/v1/S18-1086
%P 531-536
Markdown (Informal)
[LDR at SemEval-2018 Task 3: A Low Dimensional Text Representation for Irony Detection](https://aclanthology.org/S18-1086) (Ghanem et al., SemEval 2018)
ACL