UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 8 Issue 9
September-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2109419


Registration ID:
315384

Page Number

e191-e195

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Title

Class imbalanced detection of sarcasm in social networking websites based on minority up-weighting

Abstract

Over the past few decades, the evolution of machine learning has been tremendous, which gave solutions to many real-world problems and still making lives more comfortable as well as innovative. One of the applications of machine learning would be to detect sarcasm in social media like Twitter, Facebook etc., which will, in turn, give us insight into a topic trending in social networking websites. Thus this mining of people’s opinions would be of use to make decisions in many ways. But due to the highly imbalanced classes of social media data, it is often difficult to get the accuracy that is desired. So, to deal with this type of dataset, in this study, synthetic minority oversampling based methods are proposed. The main focus of this article is minority up-weighting, hence, two methods namely KMeansSMOTE and BorderlineSMOTE algorithm are used along with classifiers like Bernoulli Naive Bayes (BNB), Multilayer Perceptron (MLP) and Decision Tree Classifier (DTC) to get better accuracy while dealing with imbalanced dataset. Thus this article contains an analysis of imbalanced classification in the detection of sarcasm in social media through minority up-weighting techniques.

Key Words

Machine Learning, Sarcasm Detection, Imbalanced Class, Minority Up-Weighting

Cite This Article

"Class imbalanced detection of sarcasm in social networking websites based on minority up-weighting", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 9, page no.e191-e195, September-2021, Available :http://www.jetir.org/papers/JETIR2109419.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Class imbalanced detection of sarcasm in social networking websites based on minority up-weighting", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 9, page no. ppe191-e195, September-2021, Available at : http://www.jetir.org/papers/JETIR2109419.pdf

Publication Details

Published Paper ID: JETIR2109419
Registration ID: 315384
Published In: Volume 8 | Issue 9 | Year September-2021
DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.28190
Page No: e191-e195
Country: Kolkata, West Bengal, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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