Combining Machine Learning Techniques to Detect Cyberbullying in Twitter: A Hybrid Approach

Abstract: With The rise of social media platforms has led to an increase in cyberbullying, a form of bullying that takes place online. To combat this problem, a hybrid machine learning model is proposed to detect cyberbullying on the Twitter social media network. The model combines traditional machine learning algorithms such as Support Vector Machines (SVM) and Logistic Regression (LR). This model has the potential to be extended to other social media platforms and can be used by social media companies to improve their content moderation policies and practices. By identifying and removing cyberbullying content, social media companies can create a safer online environment for their users.

Keywords: Support Vector Machine (SVM), Logistic Regression (LR), Machine Learning (ML), Text Classification (TC), Natural Language Processing (NLP), Cyber Bullying (CB).