In the framework of EUNOIA project we are currently gathering information related to mobility. The aim is to study mobility behavior of people in urban areas , such as attitudes and lifestyle, which are particularly important, e.g., for developing demand management concepts aiming to influence mobility decisions.
In this context we are using geolocalized tweets as a source of information form mobility patterns. In order to collect this data we make use of Python and Tweepy. Storing this data and accessing to them quickly is a challenging task for which we rely on MongoDB and the Python plugging for it. Analysis and visualization are achieved by using raw Python code, networkx and matplotlib. And finally, the Python web framework Django is used to share the data between the project partners.