This study explores tourists' behavioral patterns in Bali's top-rated destinations by integrating multiclass text classification and network analysis. The research focuses on tourists' perceptions and mobility, aiming to uncover their behavioral patterns through reviews and movement patterns. The study finds that destinations generally receive positive feedback, with 80.36% positive reviews, with natural attractions being the most positive aspect and infrastructure the least positive. The analysis highlights that qualitative experiences do not always align with quantitative cost-effectiveness evaluations. Through network analysis, the study identifies three clusters of attractions catering to diverse preferences, emphasizing the need for tourism destinations to adapt to varied tourist expectations to enhance appeal and satisfaction. The research underscores the importance of understanding tourists' cognitive image perceptions and their mobility patterns to improve destination management and service offerings.This study explores tourists' behavioral patterns in Bali's top-rated destinations by integrating multiclass text classification and network analysis. The research focuses on tourists' perceptions and mobility, aiming to uncover their behavioral patterns through reviews and movement patterns. The study finds that destinations generally receive positive feedback, with 80.36% positive reviews, with natural attractions being the most positive aspect and infrastructure the least positive. The analysis highlights that qualitative experiences do not always align with quantitative cost-effectiveness evaluations. Through network analysis, the study identifies three clusters of attractions catering to diverse preferences, emphasizing the need for tourism destinations to adapt to varied tourist expectations to enhance appeal and satisfaction. The research underscores the importance of understanding tourists' cognitive image perceptions and their mobility patterns to improve destination management and service offerings.