SENTIMENT ANALYSIS OF PUBLIC OPINION ON THE IMPACT OF DEEPFAKE TECHNOLOGY USING THE NAIVE BAYES METHOD ON PLATFORM X

Luh Deck Vera Anggreni; I Gusti Ayu Agung  Mas Aristamy; Ketut Laksmi Maswari; Made Leo Radhitya; I Putu Agus Eka Darma Udayana

Authors

Luh Deck Vera Anggreni Institut Bisnis dan Teknologi Indonesia
I Gusti Ayu Agung Mas Aristamy Institut Bisnis dan Teknologi Indonesia
Ketut Laksmi Maswari Institut Bisnis dan Teknologi Indonesia
Made Leo Radhitya Institut Bisnis dan Teknologi Indonesia
I Putu Agus Eka Darma Udayana Institut Bisnis dan Teknologi Indonesia

Keywords:

Deepfake, Sentiment Analysis, Naive Bayes, X(Twitter), Artificial Intelligence

Abstract

The development of deepfake technology, a digital manipulation tool powered by artificial intelligence, has posed significant challenges in the modern era, particularly concerning individual privacy and reputation. This technology enables the creation of highly realistic visual content, making it vulnerable to misuse, as seen in the case of Taylor Swift, who faced the unauthorized dissemination of fake explicit content on the social media platform X (Twitter). This study aims to analyze public sentiment regarding the incident using the Naive Bayes method, chosen for its reliability in text classification, low complexity, and accuracy. The research process includes data crawling, preprocessing (cleansing, case folding, tokenizing, stopword removal, and stemming), sentiment labeling with the Vader Lexicon, and TF-IDF weighting to build the classification model. The results indicate that the Naive Bayes model achieved an accuracy of 76%, precision of 79%, recall of 73%, and an F1-score of 75%. It also revealed that the majority of public sentiment was negative (60.88%), while positive sentiment accounted for 30.12%, reflecting widespread concern over the potential misuse of deepfake technology. This study offers valuable insights into public perception and provides a foundation for developing policies to mitigate the risks associated with deepfake misuse.

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