Comparison of Tiktok User Sentiment Analysis Accuracy with Naïve Bayes and Support Vector Machine

Abstract

This study aims to compare the accuracy of the sentiment analysis of TikTok application users using the Naïve Bayes algorithm and the Support Vector Machine. The data set in this study comes from comments from Tiktok users on Twitter social media. Comparison of the accuracy of sentiment analysis in this study was carried out through three tests. The first test was conducted on 848 tweets, the second test used 957 tweet data, and the third test used 1,925 tweet data. Testing is done by dividing the data by 70% for training data and 30% for test data. The results showed that the accuracy of the Naive algorithm was 89.35% and 94.08% using the Support Vector Machine algorithm.