Cyberbullying Avoidance and Impact from Online Tweets
M. Venkata Swamy, Jagadeesh Gopalakrishnan, Dhanushini Dhasarathan, Wilson Christo, Shanmugasundaram Hariharan, Vinay Kukreja · 2023
Cyberbullying has created a negative impact on people which directly or indirectly caused psychological setback in mind thought, especially youth. This has led to investigations on a wider group of research communities to focus on this major issue. The problem identified is aimed at addressing harassment on social media and several other wider cyber perspectives. This research work proposes an advanced methodology to detect cyberbullying posts using machine learning algorithms. The proposed research uses the help of three algorithms namely Convolutional Neural Network (CNN), Naïve Bayes (NB), and Support Vector Machine (SVM). The observations recorded out of the study seems to be have strong influence and lead to gain in classifying cyberbullying using CNN, due to stronger influence on understanding the tweets as compared to NB and SVM. The algorithm proved its significance with accuracy level of 90.7% using CNN approach.