Journal of Advances in Developmental Research

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Volume 17 Issue 1
2026

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Detection of Cyberbullying on Social Media using Machine Learning

Author(s) M. Sarada, M. Indu, M. Vasavi Guru Harshini, N. Sucharitha, B. Javeed Basha
Country India
Abstract The problem of cyberbullying is one of the most significant threats of the digital age when individuals of any age can easily fall victim to it, and it can cause not only emotional stress and depression but in severe cases, can result in self-harm and suicide. The need of an efficient content monitoring and moderation system has become very high, in association with the fast rise of social media sites. The paper is aimed at defining different types of cyberbullying based on the data provided in two significant sources: hateful and abusive tweets on Twitter and personal comments on attacks on the Wikipedia discussion forums. Such data sets are used to learn about various trends of internet harassment among sites. In order to ensure the detection of harmful content is done with reasonable precision there were three feature extraction methods employed to process and represent textual data and four machine learning classifiers which were applied to identify the best detection model. The performance of the system was assessed according to common metrics and the level of results indicated high effectiveness. The optimal model attained above 90 percentage rate in twitter data and above 80 per cent rate in Wikipedia data. The results demonstrate the opportunities of machine learning-related solutions in enhancing the level of online safety and advancing the creation of credible content moderation frameworks.
Keywords cyberbullying, machine learning, convolutional neural network, deep learning, feature extraction, text classification.
Field Engineering
Published In Volume 17, Issue 1, January-June 2026
Published On 2026-04-04
Cite This Detection of Cyberbullying on Social Media using Machine Learning - M. Sarada, M. Indu, M. Vasavi Guru Harshini, N. Sucharitha, B. Javeed Basha - IJAIDR Volume 17, Issue 1, January-June 2026.
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