ENHANCING HATE SPEECH/TOXIC COMMENT DETECTION USING ML & DL TECHNIQUES

Registration ID: IJNRD_204928

Published ID: IJNRD2309083

DOI: Click Here to Get

Korupolu Prudhvi Raj Naidu , G. Sharmila Sujatha

Hate Speech, Toxic Comment Detection, Machine Learning, Deep Learning

With the rise in internet users due to improved telecommunication networks and affordable data rates, people from remote areas can now freely express their thoughts and opinions online. However, this increase in internet usage has also led to a concerning surge in hate speech and bullying. These negative behaviors hinder open expression, promote negativity, depression, and fuel communal/racial hatred, sometimes even leading to riots. Social media platforms must take proactive steps to ensure a toxic-free environment. By fostering a safe space, these platforms can encourage the free exchange of information and diverse opinions. This paper addresses the challenge of controlling hate speech and toxic comments on social media platforms. It develops models using multi-class and multi-label classification techniques to automatically detect and flag harmful content. Real comments from social media platforms are used to create a representative dataset. The study explores machine learning and deep learning models. Performance metrics are used to compare the effectiveness of the models. The paper aims to create a safer online environment by mitigating the negative impact of hate speech and toxic comments.

Published Paper   E-Certificate

Korupolu Prudhvi Raj Naidu & G. Sharmila Sujatha (September-2023). ENHANCING HATE SPEECH/TOXIC COMMENT DETECTION USING ML & DL TECHNIQUES. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(9), a700-a716. https://ijnrd.org/papers/IJNRD2309083.pdf

Volume 8 Issue 9, September-2023

Pages : a700-a716

Paper Reg. ID: IJNRD_204928

Published Paper Id: IJNRD2309083

Downloads: 000121996

Research Area: Engineering

Country: visakhapatnam, andhra pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2309083.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2309083

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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