Sentiment Analysis of Cyberbullying in Social Media UsingDecision Trees
Aliza Sharina Sulaiman · UTPedia (Universiti Teknologi Petronas) · 2020
The given paper describes modern approach to the task of sentiment analysis of cyberbullying in social media by using decision trees. These methods are based on statistical models, which are a machine learning algorithms. Using social media nowadays, age has grown significantly in our personal lives. People like to share their experiences in public social media sites with their friends. This has also risen the possibilities and advancement of security threats. This study uses data mining techniques from the views of users written ion Twitter to use in sentiment analysis of decision tree classification. The study used different keyword to extract users’ thoughts or feelings through their tweets. KNIME is also used to assist in making analysis sentiments by using three different datasets with the Decision Tree approaches.