@inproceedings{hantsch-chkroun-2022-connotation,
title = "connotation{\_}clashers at {S}em{E}val-2022 Task 6: The effect of sentiment analysis on sarcasm detection",
author = "Hantsch, Patrick and
Chkroun, Nadav",
editor = "Emerson, Guy and
Schluter, Natalie and
Stanovsky, Gabriel and
Kumar, Ritesh and
Palmer, Alexis and
Schneider, Nathan and
Singh, Siddharth and
Ratan, Shyam",
booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.semeval-1.132/",
doi = "10.18653/v1/2022.semeval-1.132",
pages = "945--950",
abstract = "We investigated the influence of contradictory connotations of words or phrases occurring in sarcastic statements, causing those statements to convey the opposite of their literal meaning. Our approach was to perform a sentiment analysis in order to capture potential opposite sentiments within one sentence and use its results as additional information for a further classifier extracting general text features, testing this for a Convolutional Neural Network, as well as for a Support Vector Machine classifier, respectively. We found that a more complex and sophisticated implementation of the sentiment analysis than just classifying the sentences as positive or negative is necessary, since our implementation showed a worse performance in both approaches than the respective classifier without using any sentiment analysis."
}
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%0 Conference Proceedings
%T connotation_clashers at SemEval-2022 Task 6: The effect of sentiment analysis on sarcasm detection
%A Hantsch, Patrick
%A Chkroun, Nadav
%Y Emerson, Guy
%Y Schluter, Natalie
%Y Stanovsky, Gabriel
%Y Kumar, Ritesh
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y Singh, Siddharth
%Y Ratan, Shyam
%S Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F hantsch-chkroun-2022-connotation
%X We investigated the influence of contradictory connotations of words or phrases occurring in sarcastic statements, causing those statements to convey the opposite of their literal meaning. Our approach was to perform a sentiment analysis in order to capture potential opposite sentiments within one sentence and use its results as additional information for a further classifier extracting general text features, testing this for a Convolutional Neural Network, as well as for a Support Vector Machine classifier, respectively. We found that a more complex and sophisticated implementation of the sentiment analysis than just classifying the sentences as positive or negative is necessary, since our implementation showed a worse performance in both approaches than the respective classifier without using any sentiment analysis.
%R 10.18653/v1/2022.semeval-1.132
%U https://aclanthology.org/2022.semeval-1.132/
%U https://doi.org/10.18653/v1/2022.semeval-1.132
%P 945-950
Markdown (Informal)
[connotation_clashers at SemEval-2022 Task 6: The effect of sentiment analysis on sarcasm detection](https://aclanthology.org/2022.semeval-1.132/) (Hantsch & Chkroun, SemEval 2022)
ACL