Using Location-Based Social Network Data and Urban Topological Analyses for Predicting City Center Expansion Zones

Abstract

This paper introduces an ongoing study that aims to combine location-based social network analyses and topological space syntax analyses for reading the city and developing urban strategies, compatibly with city center expansion trends. This study focuses on: a) Analyzing/visualization of the big data that emerged from location-based social networks that exposes activity trends of the study area. b) Revealing relationships between activity distribution and potential movement axes - that achieved through space syntax analysis- c) Evaluating potential movement axes and activity trend relations for reasoning urban decision making.