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Reseach Article

Logistic Regression Method for Sarcasm Detection of Text Data

by Bipin Gupta, Ankur Gupta
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 26
Year of Publication: 2019
Authors: Bipin Gupta, Ankur Gupta
10.5120/ijca2019919451

Bipin Gupta, Ankur Gupta . Logistic Regression Method for Sarcasm Detection of Text Data. International Journal of Computer Applications. 177, 26 ( Dec 2019), 1-4. DOI=10.5120/ijca2019919451

@article{ 10.5120/ijca2019919451,
author = { Bipin Gupta, Ankur Gupta },
title = { Logistic Regression Method for Sarcasm Detection of Text Data },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2019 },
volume = { 177 },
number = { 26 },
month = { Dec },
year = { 2019 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number26/31058-2019919451/ },
doi = { 10.5120/ijca2019919451 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:46:56.746649+05:30
%A Bipin Gupta
%A Ankur Gupta
%T Logistic Regression Method for Sarcasm Detection of Text Data
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 26
%P 1-4
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The prediction analysis is approach which can predict future possibilities. This research work is based on the sarcasm detection from the text data. In the previous time SVM classification is applied for the sarcasm detection. The SVM classifier classifies data based on the hyper plane which give low accuracy. To improve accuracy for sarcasm detection logistic regression is applied in this work. The existing and proposed techniques are implemented in python and results are analyzed in terms of accuracy, execution time. The proposed approach has high accuracy and low execution time as compared to SVM classifier for sarcasm detection

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Index Terms

Computer Science
Information Sciences

Keywords

SVM Logistic Regression Sarcasm detection