Paper Title

Hate Text Detection API Using LSTM-Deep Learning.

Authors

Rayyan Mulla , Vedant Mate , Rohitkumar Singh , Yash Roham , Prof.Suchitra Deokate

Keywords

Hatetextdetection , Hatespeechdetection ,MLproject , DeepLearningproject , AIML ,

Abstract

The rapid rise of digital communication has led to increase of harmful online content, making hate text detection a very important necessity. This project focuses on building a Hate Text Detection API using Natural Language Processing (NLP) and deep learning techniques to automatically identify and classify hate text in textual data. The API makes use of the Recurrent Neural Networks (RNNs) or Long Short-Term Memory (LSTM) networks to effectively capture contextual relationships in text, enabling accurate real-time detection of offensive text. It makes use of Python and FastAPI, the API offers high performance, scalability, and easy integration with other applications. It consists endpoints that allow users to submit text for analysis and receive detailed responses categorizing the detected hate text. The system is hosted on Google Cloud Services to ensure reliability and scalability, making it suitable for handling largescale data. This project shows how NLP and deep learning can be applied to combat hate text and create safer online communities through efficient, automated moderation tools.

How To Cite

"Hate Text Detection API Using LSTM-Deep Learning. ", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.12, Issue 4, page no.b15-b20, April-2025, Available :https://tijer.org/TIJER/papers/TIJER2504142.pdf

Issue

Volume 12 Issue 4, April-2025

Pages : b15-b20

Other Publication Details

Paper Reg. ID: TIJER_157635

Published Paper Id: TIJER2504142

Downloads: 000296

Research Area: Science and Technology

Country: Pune, Maharashtra, India

Published Paper PDF: https://tijer.org/TIJER/papers/TIJER2504142

Published Paper URL: https://tijer.org/TIJER/viewpaperforall?paper=TIJER2504142

About Publisher

ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: TIJER (IJ Publication) Janvi Wave

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