Digigtal Signs of the neighbourhoods

Abstract

With the popularity of different social media platforms, the amounts of data recorded might be seen as an opportunity to fulfill needs of city management. Strugglyng multiple challenges, city gouverneurs are eager to get real-time data in order to understand what is happening in the city and reinforce their decisions. In our study, we investigate how Twitter stream might be used to characterize urban areas and predict their socioeconomic properties. As result, several directions of potential implementation were defined, including event detection and evaluation, areas partitioning and profiling, and prediction of areas socio-economic properties.