UGC Approved Journal no 63975(19)

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

Volume 10 Issue 5
May-2023
eISSN: 2349-5162

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

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Published Paper ID:
JETIR2305D73


Registration ID:
516474

Page Number

n504-n508

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Title

A Deep Learning Approach for Hate Speech Spreaders Detection using Statistical and Contextualized Embeddings

Abstract

As the social network usage increases, hate speech is also increasing. An automated method to detect hate speech spreaders is needed. There have been many methods but each has its own limitations. Some of them are restricted to language, some need high computational power, and some does not consider the context. So, we tried various statistical and contextual embeddings paired with standard deep learning classifiers. This experiment carried out with the PAN competition 2021 dataset of hate speech spreaders detection task. For English language dataset, the Ensemble model using CNN obtained best training accuracy of 0.70 for hate speech spreaders detection and best testing accuracy of 0.73 for hate speech spreaders detection when compared with other models. For Spanish language dataset, the Ensemble model using CNN obtained best training accuracy of 0.90 for hate speech spreaders detection and the Trained Embeddings + CNN obtained best testing accuracy of 0.80 for hate speech spreaders detection when compared with other models.

Key Words

Hate Speech Spreaders, Word Embeddings, CNN, DistilBERT, TFIDF, Bi-LSTM

Cite This Article

"A Deep Learning Approach for Hate Speech Spreaders Detection using Statistical and Contextualized Embeddings", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.n504-n508, May-2023, Available :http://www.jetir.org/papers/JETIR2305D73.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

"A Deep Learning Approach for Hate Speech Spreaders Detection using Statistical and Contextualized Embeddings", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppn504-n508, May-2023, Available at : http://www.jetir.org/papers/JETIR2305D73.pdf

Publication Details

Published Paper ID: JETIR2305D73
Registration ID: 516474
Published In: Volume 10 | Issue 5 | Year May-2023
DOI (Digital Object Identifier):
Page No: n504-n508
Country: Guntur, Andhra Pradesh, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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