Strategy for Extraction of Foursquare’s Social Media Geographic Information Through Data Mining

Abstract

This aim of this paper is the acquisition of geographic data from the Foursquare application, using data mining to perform exploratory and spatial analyses of the distribution of tourist attraction and their density distribution in Rio de Janeiro city. Thus, in accordance with the Extraction, Transformation, and Load methodology, three research algorithms were developed using a tree hierarchical structure to collect information for the categories of Museums, Monuments and Landmarks, Historic Sites, Scenic Lookouts, and Trails, in the foursquare database. Quantitative analysis was performed of check-ins per neighborhood of Rio de Janeiro city, and kernel density (hot spot) maps were generated The results presented in this paper show the need for the data filtering process - less than 50% of the mined data were used, and a large part of the density of the Museums, Historic Sites, and Monuments and Landmarks categories is in the center of the city; while the Scenic Lookouts and Trails categories predominate in the south zone. This kind of analysis was shown to be a tool to support the city's tourist management in relation to the spatial localization of these categories, the tourists’ evaluations of the places, and the frequency of the target public.