As urban tourism becomes an indispensable part of urban dynamics, tourist attractions are increasingly woven into residents’ everyday living spaces. However, the spatial patterns of, and level of mix between tourist and local attractions have remained largely unknown. Taking advantage of the recent development in volunteered geographic information, we used Flickr data to examine how tourists and locals’ destinations overlap spatially. We combined a density-based spatial clustering algorithm, a dissimilarity index, spatial scan statistics, and location-based tag clouds to explore the potential spatial and social interactions between tourists and local residents in ten US cities: Atlanta, Boston, Chicago, Houston, Los Angeles, New York City, Orlando, San Francisco, Seattle, and Washington, D.C.. At the city-level, we report the spatial distributions of visitors’ and locals’ destinations and compare the overall level of segregation between the two groups. Within each city, we identify the hotspots for visitors and locals and investigate the semantic content for reasons behind visiting specific places. Finally, we discuss our findings and provide implications for urban planning and tourism research.