Sentiment Analysis of Twitter Comments on Manchester United's Performance Using the Support Vector Machine Algorithm
https://doi.org/10.58466/aicoms.v3i1.1511
Keywords:
Analis Sentimen, Manchester United, komentar, Support Vector Machine, twitterAbstract
Manchester United is one of the largest clubs in the English Premier League with an exceptional history in European and global football. In the 2023/2024 season, Manchester United experienced a very poor season, leading to various positive and negative sentiments from its fans, especially on social media. Sentiment data was gathered from Twitter, where Manchester United fans expressed their opinions regarding the team's performance in the Premier League. This study employs the Support Vector Machine (SVM) method to process and classify data collected from Twitter, aiming to analyze the sentiments of Manchester United fans based on their social media comments. The results indicate that the performance of the Support Vector Machine is relatively poor, achieving an accuracy of 58.73%. This is due to the dataset relying on a single keyword, which led to suboptimal and less complex data, resulting in the Support Vector Machine (SVM) producing relatively low accuracy.
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