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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM37403
Volume:
8 |
9 |
Sep 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
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.
Bullying or harassment that takes place online is known as cyberbullying or cyber harassment. Online bullying also refers to cyberbullying and cyber harassment. Repeated behaviour and an intention to cause harm are indicators of bullying or harassment. Cyberbullying victims may have reduced self- esteem, more suicide thoughts, and other unfavourable emotions including anxiety, frustration, anger, or depression. Our project is about detecting these hateful comments using a machine learning algorithm and classifying them into 2 levels based on their severity like “low” and “High” levels. Social media has become a very important part of our lives, especially after the pandemic. It has been used by people in all age groups as a way of communication. Even though it is making our life so much easier, it also has its downsides. In this project, we will address one of such issues, it is evident that social media is to share opinions but sometimes it gets out of hand. Hateful comments can affect people’s physical and mental health. This is something we have come across in our day-to-day life, and the solution we have come up with is to detect such comments and take action against them. We are using a Machine Learning algorithm to detect hateful comments and their severity to take action depending on it.
KEYWORDS
Publication Date
11/8/2024
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.
Funding Information
No funding information available for this research.
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