International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 3 (May-June 2025) Submit your research before last 3 days of June to publish your research paper in the issue of May-June.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 7 Issue 3
May-June 2025

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Hate Crimes Detection on Twitter using ML Techniques

Author(s) Mr. Subodh Mahadev Sawale, Mrs Ashwini Garkhedkar
Country India
Abstract With the sizeable adoption of social media structures which includes Twitter, the dissemination of hateful content material targeting people or agencies primarily based on race, gender, faith, or ethnicity has become increasingly commonplace. Manual moderation techniques are not scalable due to the sizable and swiftly developing extent of consumer-generated content material. This have a look at proposes a system studying-based framework to robotically stumble on and classify hate speech on Twitter.
The pipeline entails comprehensive textual content preprocessing— normalization, tokenization, stopword elimination, and lemmatization— accompanied by using TF-IDF-primarily based characteristic extraction. Four type models—Logistic Regression, Support Vector Machine (SVM), Naive Bayes, and Random Forest—are evaluated the usage of a publicly to be had categorised Twitter dataset. Results suggest that SVM and Random Forest provide superior overall performance in terms of precision, don't forget, and basic accuracy. This paintings highlights the effectiveness of computerized methods in moderating dangerous on-line content and lays the foundation for
destiny upgrades along with multilingual support and real-time detection.
Keywords Hate Speech Detection, Twitter Analysis, Machine Learning Algorithms, Text Classification, Social Media Monitoring, Natural Language Processing, TF- IDF, SVM, Random Forest, Crimes.
Field Computer Applications
Published In Volume 7, Issue 3, May-June 2025
Published On 2025-06-19
DOI https://doi.org/10.36948/ijfmr.2025.v07i03.47785
Short DOI https://doi.org/g9qxch
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 7 Isu 3Cover Page Vol 7 Isu 2Cover Page Vol 7 Isu 1

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com