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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM22079

FIGHT BACK CYBERBULYYING WITH NLP ON SNS USING CODE TEXT APPROACH

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM22079

Volume:

7 |

5 |

May 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
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

KG

Kunal Gupta

KG

Kanchan Ghule

AD

Ankita Dhondge

SD

Shruti Dive

ASR

Aniruddha S. Rumale

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Abstract

This research paper is about the important problem of rising hate and offensive Contents made against people or communities on social media is addressed by this proposed system. With the increasing use of social media, cyberbullying behaviour has received more and more attention. Cyberbullying may cause many serious and negative impacts on a person’s life and even lead to teen suicide. To reduce and stop cyberbullying, one effective solution is to automatically detect bullying content based on appropriate machine learning and natural language processing techniques. The impacts of cyber bullying on social media are horrifying, sometimes leading to the death of some unfortunate victims. The behaviour of the victims also changes due to this, which affects their Emotions, self-confidence and a sense of fear is also seen in such people. Thus, a complete solution is required for this problem. Cyber bullying needs to stop. The problem can be tackled by detecting and preventing it by using a machine learning approach, this needs to be done using a different perspective.

KEYWORDS

Hate Speech Social Networking Site Natural Language Processing Text Classification Machine Learning

Cite This Article

Kunal Gupta, Kanchan Ghule, Ankita Dhondge, Shruti Dive, Aniruddha S. Rumale, "FIGHT BACK CYBERBULYYING WITH NLP ON SNS USING CODE TEXT APPROACH," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 5, May 2023. https://doi.org/10.55041/IJSREM22079

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Publication Date

5/29/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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5

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The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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