Given the rapid evolution of information technology increases the number of individual tourists who choose to enjoy free travel without depending on guidebooks and tour agency services. Information sharing activities continue without limitation facilitate most tourists to explore and independently decide their destinations based on online traveler review pages. This freedom generates an increasingly complex tourist visiting pattern. On other side, the abundance of data provides a new approach in analyzing this visiting pattern. We processed 214,228 reviews written by tourists all over the world regarding tourist destinations in Bali, Indonesia. This research analyzes the online traveler review data through association rule mining techniques to detect pairs of tourist’s destinations and mapped them through the network analysis approach. We separate our exploration by tracing the tourist visiting movement as the underlying factor to understand tourist visiting behavior. We discovered the most popular tourist destination pair in one trip is Tegalalang Rice Terrace and Sacred Monkey Forest Sanctuary, and there are differences in tourist visit preferences for each tourist origin continent but still have identical main choices. This research contributes to supporting efficient mobility in tourism management by providing tourism destination networks insight.