Geospatial Sentiment Analysis Using Twitter Data on Natural Disasters in Indonesia with Support Vector Machine (SVM) Algorithm - Dalam bentuk pengganti sidang - Artikel Jurnal

Twitter serves as a crucial platform for expressing public sentiment during natural disasters, yet understanding and addressing these sentiments remains challenging due to data volume, imbalance, and regional disparities in response. This study aims to bridge this gap by conducting geospatial sentiment analysis on 988 labeled tweets related to the eruption of Mount Marapi, categorized into