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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM26837

Identification of Cyberbullying in Social Media using Machine Learning

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM26837

Volume:

7 |

11 |

Nov 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

PD

Prof.Sagar Dhanake

AD

Adesh Dorge

GH

Ganesh Hande

AG

Akshay Gaykar

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Abstract

In the modern era, the usage of internet has increased tremendously which in turn has led to the evolution of large amount of data .Cyber world d has its own pros and cons. One of the alarming situations in web 4.0 is cyber bullying a type of cyber-crime. When the bullying occurs on line with the aid of technology it is known as cyber bullying. This research paper have surveyed the work done by 30 different researchers on cyber bullying, and elaborated on different methodologies adopted by them for the detection of bullying, and how you protect the community from online evil act of cyber bullying. Cyber- crimes involve all the crimes where internet is used as an access medium and committed through some electronic device such as computers and mobile phones. Unavailability of datasets, hidden identity of predators and the privacy of the victims are the main factors for limiting the past research in cyberbullying detection.

KEYWORDS

cyberbullying machine learning victim social media dataset.

Cite This Article

Prof.Sagar Dhanake, Adesh Dorge, Ganesh Hande, Akshay Gaykar, "Identification of Cyberbullying in Social Media using Machine Learning," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 11, Nov 2023.

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Publication Date

11/19/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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Conflict of Interest

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

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