Speaker
Description
Human mobility in megacities is a fundamental problem to address and one of the most pressing societal challenges nowadays. Fortunately, we have now at our disposal a vast set of data, through mobile devices and geolocalized social networks, that allow us to explore, using Data Science, the patterns of mobility of tens of millions of people on a daily basis. We present here recent result for 415 cities in 77 countries using a big data set of the social network Foursquare. Mining this data set we obtained patterns of visitation of attractive sites in megacities that work as a proxy for mobility. We explore these patterns using Artificial Intelligence and Machine Learning to classify and predict statistically mobility patterns according to socio-economic and cultural variations in hundreds of cities around the world.
