Analysis sentiment about islamophobia when Christchurch attack on social media

Abstract

Islamophobia is formed by "Islam" with "-phobia" which means "fear of Islam". This shows the view of Islam as "other" and can threaten Western culture. The recent horrific terror attack that took place at the Christchurch mosque in New Zealand, is the result of allowing an attitude of hatred towards Islam in the West. Twitter is social media that allows users send real-time messages and can be used for sentiment analysis because it has a large amount of data. The lexical based method using VADER is used for automatic labeling of crawling data from Twitter. And then compare Supervised Machine Learning Naïve Bayes and SVM algorithm. Addition of SMOTE for Imbalanced Data. As result, SVM with SMOTE is proven the highest performance value and short processing time.