Analisis Sentimen Facebook & Instagram tentang Pilgub NTB 2024 dengan Algoritma SVM - Adnia Tujahidah; M.Julkarnain; Atmawan Oktavia, Siska; Yunanri. W; Esabella, Shinta (Management of Information System Journal, 2025)
The 2024 West Nusa Tenggara (NTB) gubernatorial election has become a major public spotlight, particularly on social media platforms such as Facebook and Instagram, where citizens actively express political opinions. This study aims to (1) describe the sentiment of NTB society toward gubernatorial candidates through social media, and (2) analyze the “headspit” phenomenon and its influence on public sentiment using the Support Vector Machine (SVM) algorithm. Data consisting of comments, captions, and interactions from accounts such as @SuaraNTB, @KpuNTB, and @MediaNTB were collected through a scraping process. The analysis followed the Knowledge Discovery in Database (KDD) approach, including data selection, preprocessing, transformation, classification, and evaluation. The results reveal three sentiment categories, with one being dominant, and illustrate the dynamics of digital political interaction and the emergence of headspit during the NTB 2024 gubernatorial campaign.