Analysis Sentiment Cyberbullying In Instagram Comments with XGBoost Method
Abstract
Technological developments make social media widely used by the general public, which causes negative impacts, one of which is cyberbullying. Cyberbullying is an act of insulting, humiliating another person on social media. A system that can detect cyberbullying because of the large amount of information circulating on social media is impossible for humans to visit. One suitable method to solve this problem is Extereme Gradient Boosting (XGBoost). XGBoost was chosen because it can run 10 times faster than other Gradient Boosting methods. The process of changing sentences into vectors uses the TF-IDF method. The TF/IDF method is known as a simple but relevant algorithm in doing words on a document. XGBoost accepts input in the form of vectors obtained from the TF-IDF process. In this research, there are 1452 comments which will be broken down into training data and testing data. By using XGBoost and TF-IDF methods, the accuracy is 75.20%, precision is 71%, recall is 87%, and F1-score is 78%.
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