A Voting Enabled Predictive Approach for Hate Speech Detection

Title

A Voting Enabled Predictive Approach for Hate Speech Detection

Creator

Panda P.; Mishra S.; Sharma V.; Alkhayyat A.

Description

In today's digital environment, hate speech, which is defined as disparaging and discriminating communication based on personal characteristics, presents a big difficulty. Hate crimes and the rising amount of such content on social media platforms are two examples of how it is having an impact. Large volumes of textual data require manual analysis and categorization, which is tedious and subject to prejudice. Machine learning (ML) technologies have the ability to automate hate speech identification with increased objectivity and accuracy in order to overcome these constraints. This article intends to give a comparative analysis of various ML models for the identification of hate speech. The proliferation of such content online and its negative repercussions on people and society are explored, as is the necessity for automated hate speech recognition. This paper intends to support the creation of efficient hate speech detection systems by performing a comparative analysis of ML models. Random forest records the best performance with higher accuracy and low response delay period for hate speech detection. The results will help enhance automated text classification algorithms and, in the end, promote a safer and more welcoming online environment by illuminating the benefits and drawbacks of various approaches. 2023 IEEE.

Source

Proceedings of International Conference on Contemporary Computing and Informatics, IC3I 2023, pp. 450-454.

Date

2023-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

CountVectorizer; Hate speech detection; logistic regression; machine learning; Naive Bayes classifier; Random Forest classifier

Coverage

Panda P., School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, India; Mishra S., School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, India; Sharma V., CHRIST (Deemed to Be University), Computer Science Department, Delhi NCR, India; Alkhayyat A., College of Technical Engineering, The Islamic University, Najaf, Iraq

Rights

Restricted Access

Relation

ISBN: 979-835030448-0

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/IC3I59117.2023.10397912

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187246432&doi=10.1109%2fIC3I59117.2023.10397912&partnerID=40&md5=9fab71336fe2a5e161c9d8b38b6a9362