Filtering Online Harassment: ML based Cyberbullying Detectionz

Cyber bullying has emerged as a great threat to the people on the internet. The platform, which was made for good use, is being used by some to harass people. This is actually a misuse of a great invention. Also, the nature of social media is such that these things spread very quickly due to the online communications. Many times, this spreads anonymously. Manual way of detection of cyber bullying will be very inefficient and a lot of time consuming. Thus, an automated cyber bullying detection using machine learning will come to help. This paper explores the effectiveness of various machine learning algorithms in classifying the tweets into different types of cyber bullying, including age based, ethnicity based, gender based, religious based and non cyber bullying. This automated detection using machine learning will offer a great approach to mitigate these bullying and its after effects by identifying and isolating the harmful texts and messages in real time.

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Publication Details

Journal
SAMRIDDHI A Journal of Physical Sciences Engineering and Technology
Published
2025-03-29
DOI
https://doi.org/10.18090/samriddhi.v17i01.01
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Filtering Online Harassment: ML based Cyberbullying Detectionz

Hiranmaya Mishra, Ayushman Singh, Sumit Kumar Jha
SAMRIDDHI A Journal of Physical Sciences Engineering and Technology
Advanced Malware Detection Techniques
article

Filtering Online Harassment: ML based Cyberbullying Detectionz

Hiranmaya Mishra, Ayushman Singh, Sumit Kumar Jha
article en

Abstract

Cyber bullying has emerged as a great threat to the people on the internet. The platform, which was made for good use, is being used by some to harass people. This is actually a misuse of a great invention. Also, the nature of social media is such that these things spread very quickly due to the online communications. Many times, this spreads anonymously. Manual way of detection of cyber bullying will be very inefficient and a lot of time consuming. Thus, an automated cyber bullying detection using machine learning will come to help. This paper explores the effectiveness of various machine learning algorithms in classifying the tweets into different types of cyber bullying, including age based, ethnicity based, gender based, religious based and non cyber bullying. This automated detection using machine learning will offer a great approach to mitigate these bullying and its after effects by identifying and isolating the harmful texts and messages in real time.

SAMRIDDHI A Journal of Physical Sciences Engineering and TechnologyVol. 17(01)
Motilal Nehru National Institute of Technology (IN)
Openalex Percentile: Top 83%
Advanced Malware Detection Techniques
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