Manuscript Number : SHISRRJ247211

A Multi Stage Machine Learning and Fuzzy Approach to Cyber-Hate Detection

Authors(2) :-T. Muni Kumari, Goddeti Gowri

The identification of hate speech and harmful information on digital platforms is becoming increasingly important to the upkeep of a friendly and safe online community. In this study, we describe a novel approach to cyber hate detection that blends multi-stage machine learning approaches with fuzzy logic-based analysis. Pre-processing the data, feature extraction, classification, and fuzzy inference are some of the processing stages included in the methodology. We employ two state-of-the-art machine learning algorithms, deep neural networks and ensemble techniques, to extract and classify instances of hate speech with robust features. We additionally employ fuzzy logic to capture the inherent ambiguity and uncertainty in hate speech recognition, thereby enabling more sophisticated and context-aware decision-making.

Authors and Affiliations

T. Muni Kumari
Assistant Professor, Department of MCA, Annamacharya Institute of Technology & Sciences, Tirupati, Andhra Pradesh, India
Goddeti Gowri
Post Graduate, Department of MCA, Annamacharya Institute of Technology & Sciences, Tirupati, Andhra Pradesh, India

Cyberbullying, Multi-Phase Method, CNNs, or Convolutional Neural Networks, Fuzziness in Reasoning Hate Speech Detection Group Education, Regression Using Logistic Functions Feature Extraction Machine Learning.

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Publication Details

Published in : Volume 7 | Issue 2 | March-April 2024
Date of Publication : 2024-03-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 69-75
Manuscript Number : SHISRRJ247211
Publisher : Shauryam Research Institute

ISSN : 2581-6306

Cite This Article :

T. Muni Kumari, Goddeti Gowri, "A Multi Stage Machine Learning and Fuzzy Approach to Cyber-Hate Detection", Shodhshauryam, International Scientific Refereed Research Journal (SHISRRJ), ISSN : 2581-6306, Volume 7, Issue 2, pp.69-75, March-April.2024
URL : https://shisrrj.com/SHISRRJ247211

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