Different Models to Visualise Geolocated City Data from Social Networks

Three different models for visualisation of geolocated social networks data are presented in this paper. One is based on the concept of grid computing, another uses the nearest neighbour query location and the third adopts the urban network structure itself. The models follow two different approaches. They all consider the geographic location of data, but the third one is based on the visualisation of the topology of the network where the city data are located. Hence, the first two models visualise spatial data over a map, while the third visualise specifically the urban network. With the aim to compare and evaluate the characteristics of the aforementioned visualisation models, georeferenced data from two social networks were collected: Google Places and Foursquare.