Analysis of Vina Film Sentiment on Social Media X Using The Naïve Bayes Method

Abstract

The increasingly rapid development of technology and information, one of which is the internet. Where users can share opinions and discuss various topics or problems around them, namely social media One of the news items that frequently appears as a trending topic on X is the Vina film controversy. However, with the large amount of review data available, it will be difficult to process manually. Therefore, sentiment analysis is needed to see whether people's tendencies toward the Vina film case are positive or negative. The stages carried out were data collection taken via web scrapping with an initial amount of data of 833 and processed through the preprocessing stage, including cleaning, case folding, normalization, stopword removal, tokenization, and stemming, the data became 830. The application of the Naïve Bayes algorithm in this research uses the probability method to classify and predict 664 training data and 166 test data, with the help of the Python library. The accuracy calculation results show quite good performance with TF-IDF weighting producing an accuracy of 78%, precision of 80%, and recall of 90%, f1-score of 84%. Analysis from this research shows that the dominance of negative sentiment is 517 while positive sentiment is 313. The amount and quality of training data play an important role in system quality, where high data quality provides better accuracy in predicting sentiment classes.