UGC Approved Journal no 63975(19)

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

Volume 8 Issue 10
October-2021
eISSN: 2349-5162

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

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Published Paper ID:
JETIR2110169


Registration ID:
315879

Page Number

b650-b658

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Title

SARCASM DETECTION IN TEXT USING DEEP LEARNING NETWORKS

Abstract

Textual sentiment or opinion analysis systems mine textual data to identify personal feelings or views about a particular item or event. However, if sarcastic features of conversation are not taken into account, then these systems may be biased. As a result, sarcasm detection in textual communication is important for these systems' performance. Several research have used numerous methods to identify sarcasm in text, but all lack a critical component of any textual form of communication: context and semantics. The context and semantics are captured using BERT Model. Then, the classifiers are subsequently trained using these rich context and semantic embeddings. Using two datasets, we compared our system to state-of-the-art systems and found that BERT had higher F1-score, recall, and precision. As a result, we conclude that incorporating contextual and semantic data into sarcastic classifiers increases their overall performance.

Key Words

Sarcasm detection, Classification, Semantic, BERT, embeddings, Word2Vec

Cite This Article

"SARCASM DETECTION IN TEXT USING DEEP LEARNING NETWORKS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 10, page no.b650-b658, October-2021, Available :http://www.jetir.org/papers/JETIR2110169.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

"SARCASM DETECTION IN TEXT USING DEEP LEARNING NETWORKS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 10, page no. ppb650-b658, October-2021, Available at : http://www.jetir.org/papers/JETIR2110169.pdf

Publication Details

Published Paper ID: JETIR2110169
Registration ID: 315879
Published In: Volume 8 | Issue 10 | Year October-2021
DOI (Digital Object Identifier):
Page No: b650-b658
Country: Srinagar, Jammu & Kashmir, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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