I have several datasets on mobile phone activities that can be analysed. One of them is a very comprehensive dataset referring to seven different main cities in Italy and provides information on:
- number of SMSs sent and received
- number of phone calls made and received
- volume of access to the Internet through smart phones
- aggregated demographic information: age range, gender, and post code where the SIM was registered/purchased
All of this information is provided at a time granularity of fifteen minutes and divided on geographical cells provided by the dataset. For instance, the dataset gives you the overall number of phone calls in a fifteen minutes interval for a specific cell. There is also an estimate of how many people were present in any cell at any time interval.
A starting point of the project could investigate the demographic of users and how it changes over time. Is there any interesting information that can be found by using not only the mobile phone activity but also the information on gender, age range and how many people there are in a cell? What are the different behaviours over a day, week or month, of mobile phone users depending on their age and gender?
Part of this would also involve discussing further interesting questions that may be answered through this dataset.
This project could be relevant for everyone with an interest in computational social science and willing to learn/share experience on how to deal with timestamped geographical data, shapefiles and other data analaysis tools.