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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM24471

Enhancement in Cyberbullying Detection on Social Networks using Advanced Machine Learning Techniques

Stream/Area:

-

Subject:

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Paper ID:

10.55041/IJSREM24471

Volume:

7 |

7 |

Jul 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

KM

K. MAHALAKSHMI

D

Dr.B.JAISON

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Abstract

It is an age of the Internet and high level media, and virtual diversion structures are one of the most outrageous a large part of the time used verbal exchange medium nowadays. In any case, several people use those locales for malignant reasoning and among those awful perspectives “Cyberbullying” is normal. Cyberbullying is a condition of bothering accomplished through electronic suggests and is used to insult or damage others. Various investigators have proposed answers and systems to vanquish this risk, yet joke is one part of it that also wishes to be reached. This notification wants to focus in on past researchers and to propose a procedure to find cyberbullying alongside the detail of joke canvassed in it. The outcomes showed that SVM classifier accomplished higher than different classifiers.

KEYWORDS

Online Bullying Detection NLP Naïve Bayes social media Non-bullying Text Bullying Text.

Cite This Article

K. MAHALAKSHMI, Dr.B.JAISON, "Enhancement in Cyberbullying Detection on Social Networks using Advanced Machine Learning Techniques," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 7, Jul 2023. https://doi.org/10.55041/IJSREM24471

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9/6/2023

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