| Popis: |
In the last decade digital devices and services have permeated many aspects of everyday life. They generate massive amounts of data that provide insightful information about how people move across geographic areas and how they interact with others. By analysing this detailed information, it is possible to investigate aspects of human mobility and interaction. Therefore, the thesis of this dissertation is that the analysis of mobility and interaction traces generated by digital devices and services, at different timescales and spatial granularity, can be used to gain a better understanding of human behaviour, build new applications and improve existing services. In order to substantiate this statement I develop analytical models and applications supported by three sources of mobility and interaction data: online social networks, mobile phone networks and GPS traces. First, I present three applications related to data gathered from online social networks, namely the analysis of a global rumour spreading in Twitter, the definition of spatial dissemination measures in a social graph and the analysis of collaboration between developers in GitHub. Then I describe two applications of the analysis of country-wide data of cellular phone networks: the modelling of epidemic containment strategies, with the goal of assessing their efficacy in curbing infectious diseases; the definition of a mobility-based measure of individual risk, which can be used to identify who needs targeted treatment. Finally, I present two applications based on GPS traces: the estimation of trajectories from spatially-coarse temporally-sparse location traces and the analysis of routing behaviour in urban settings. |
