Modelagem do Interesse por Áreas Urbanas Usando Redes Sociais Baseadas em Localização

Location-Based Social Networks (LBSNs) can help model users’ interests in urban areas in several ways. In the present work, we focus on Interest Networks (iNETs), which result from modeling LBSN data into graphs. The present study provides insights into which areas are frequently visited together by getting data from two distinct LBSNs, Foursquare and Google Places. Although the studied LBSNs differ in nature, with data varying in regularity and purpose, both modeled iNETs revealed similar urban behavior patterns and were likewise impacted by socioeconomic and geographic factors. Also, we discuss the development of a tool to empower urban studies and the by-products of this research.