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On-line social networks have grown quickly over the last few years andnowadays many people use them frequently. Furthermore the emergence ofsmartphones allows to access these networks any time from any physicallocation. Among the social networks, Twitter offers a particularly large set ofdata publicly available. Here we discuss the procedure to mine this data andstore it in distributed databases using Python scripts. We also illustrate howgeolocated tweets can be used to study the mobility of people in urban areas.

Mining online social networks with Python to study urban mobility