Social media resonance on destination dispersion to predict tourist behavior and travel distance using geospatial analysis

Abstract

This study investigates the influence of social media popularity on tourist destination preferences in Gunungkidul Regency, Yogyakarta, Indonesia, using an integrated big data and geographic information system (GIS) approach. Field surveys involving 504 respondents were combined with sentiment analysis of 30,432 cleaned tweets collected from X (formerly Twitter). Spatial analysis was applied to identify tourist origin patterns and destination attractiveness. The results show that neutral sentiment dominates online discussions, indicating generally positive but moderate tourist experiences. Destinations with higher popularity on social media, particularly Heha Sky View, Drini Beach, and Indrayanti Beach, attracted visitors from broader and more diverse origins. Spatial analysis also indicates stronger preferences for coastal and highland destinations. The integration of big data and GIS enhances understanding of tourism behavior and spatial destination patterns. Future studies are recommended to integrate multiple social media platforms and comparative spatial analyses to improve tourism planning and destination management.