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The paper follows-up ongoing research focusing on the potential of machine-readable data as additional knowledge in the governance of local tourism and destination management organizations (DMOs) in Slovakia. The current focus is on one classic social media (Facebook), one location-based social media (Foursquare), two hybrid travel-related platforms with partial attributes of reservation services (Google Places, TripAdvisor), and two online reservation services (Booking, Airbnb). The global aim is the usage of extracted data for the identification of additional entities with the obligation of local occupancy taxation, which is the financial backbone of Slovak (DMOs). A set of simple and globally reusable scripts constructed in Python and PostgreSQL were used to extract data on lodging providers from the Google Places application programming interface (API), the Facebook Place Search API and the Foursquare Venue API over grid overlays of districts’ spatial representation. For pure scientific purposes in the case of Tripadvisor, Booking, and Airbnb, with no suitable access to open APIs, web scraping methods were used for data extraction. The pilot case was applied in the boundaries of Kosice city (Slovakia), and the aggregations of processed data were compared with official open statistics. Results indicate that the automated continuous monitoring of online platforms could help local public administrations in decreasing occupancy tax evasions and even widen knowledge about online audiences and visitors’ satisfaction.

Can Location-Based Social Media and Online Reservation Services Tell More about Local Accommodation Industries than Open Governmental Data?