http://lattes.cnpq.br/8814983860861046; JERÔNIMO, Caio Libânio Melo.
Resumo:
The constant need for improvements in life quality of inhabitants of big cities, together
with the increasing urbanization of these centers, demands the use of technological means
for a better understanding of the dynamics of urban centers and how their inhabitants
interact in these environments. In this sense, the adoption of electronic devices equipped
with GPS systems, the human need for communication and, more recently, for Internet
connection, have brought new research opportunities and great challenges, especially due
to the huge amount of data generated by social networks. Several studies have used this
data to carry out research that seek to understand traces of human behavior, especially
with respect to urban mobility and trajectories. However, much of the research that
uses georeferenced data are restricted to spatial and temporal dimensions, disregarding
other aspects that may influence human mobility. This work proposes a model capable of
extracting mobility patterns from georeferenced messages of social networks and correlating them with social, economic and demographic indicators provided by government agencies, seeking to analyze which factors may impact in urban mobility. To evaluate the model, we used messages posted on Twitter and a set of social indicators, both related to the city of London. The results revealed the existence of correlations between mobility patterns and social indicators, especially those related to employment and income conditions, as well as ethnic and religious characteristics of the individuals under study.
