Tourists' information support is more actual than ever, objectively because tourism is one of the largest and fastest-growing economic sectors and subjectively because each tourist faces unfamiliar and dynamic environment, which he or she has to adapt to. One of the ways to deliver information support to tourist is various recommender systems. Classical way to build recommender systems requires either collection of ratings (collaborative filtering system) or extensive knowledge work on describing tourism domain and attractions of each area. However, there is another, more lightweight approach - to make recommendations based on social media analysis. This paper presents a method and an algorithm for identifying potentially interesting locati...