Sentiment Analysis of Public Opinion on Films Taylor Swift Eras Tour on the Twitter Platform Using the Machine Learning - Nova Idriani R; Annisa Dahlia; Pratiwi Ningum (IJATIS: Indonesian Journal of Applied Technology and Innovation Science, 2024)
Sentiment analysis is the understanding of opinions, feelings, or attitudes conveyed in texts, such as tweets, reviews, or other forms. The film “Taylor Swift: The Eras Tour” is trending among teenager, narrating Taylor Swift’s journey in the “Eras Tour” concert across various countries, encapsulated in a music-filled film. This has prompted research on sentiment analysis of netizens’ tweets about this film, considering the possibility of negative reviews. Three algorithms, Naïve Bayes, Decision Tree, and Random Forest. were used with an 80:20 data ratio and the SMOTE oversampling method, which is a unique in this research to ensure data sizes for the three sentiments: positive, negative, and neutral. The final result of this research is a word cloud for each sentiment towards the film, with the Decision Tree algorithm achieving the highest accuracy at 91%. The hope for future research is to implement and focus on the emotional aspect in conducting sentiment analysis.