International Journal For Multidisciplinary Research

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Detecting Cyberbullying attacks in the Social media platform using the SVM method

Author(s) A.SURIYA, G.FATHIMA
Country India
Abstract Social media platforms such as Twitter, Facebook, Instagram and also WhatsApp, they have become the preferred online platform for interaction and communication. These platforms are leads to malign activities such as Cyberbullying. Cyberbullying is a type of psychological abuse with a help of using digital Medias and digital devices in now a days and it create a significant impact on a society. Cyberbullying is becoming widely increased in now a days in young age Children’s and women. Need for a Cyberbullying detection is important In now a days. The complete solution for Cyberbullying is may not found and it would not be hundred percentage prevented but the detection of Cyberbullying is reduce the impact of Cyberbullying in the society in now a days. Cyberbullying leads to serious mental health issues (anxiety, depression, sleeping disorders). Cyberbullying has been mostly increased among the young age people. In India 45% Children’s were experiencing the Cyberbullying according to the Times of India report. In this paper we had proposed the demo method for the CB(cyberbullying) detection using machine learning using the SVM in the WhatsApp social media platform. In this method it will detected the cyberbullying words and it will alert the user with the notification. The SVM algorithm performed well during the detect and predict the cyber bully words. The accuracy level of the SVM algorithm is in this proposed model is 96%. This accuracy level shows that svm outperformed well in the detection of cyberbullying words.
Keywords Cyberbullying, , Alert, detection, SVM, WhatsApp social media.
Field Computer > Data / Information
Published In Volume 6, Issue 3, May-June 2024
Published On 2024-05-31
Cite This Detecting Cyberbullying attacks in the Social media platform using the SVM method - A.SURIYA, G.FATHIMA - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.21431
DOI https://doi.org/10.36948/ijfmr.2024.v06i03.21431
Short DOI https://doi.org/gtw6rv
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