Sentiment Analysis towards Full Movie Dirty Vote 2024 in X Using Support Vector Machine Method

Abstract

The development of communication technology has changed the way people express their opinions and opinions. Social media, like X, has become a means of sharing information and opinions on various topics, including films. This research analyzes sentiment towards the film "Dirty Vote 2024" using the Support Vector Machine (SVM) method. The data used is 1500 tweets collected using the Tweepy library. The tweets are then labeled as positive or negative based on the resulting sentiment value. Analysis is carried out through a text mining process which involves tokenization, labeling and weighting of words before classification using SVM. The classification results show the model's accuracy in dividing sentiment into two classes: positive and negative, which can provide valuable input for filmmakers.