Date: Friday December 16th at 2pm
Place: ENS de Lyon (Site Descartes) in Amphitheatre Descartes.
This thesis is interdisciplinary, I will present some results in Network Science, Dynamic Graphs but also Sociology, Economy and Geography. For this reason, it was important for me to organize it in Descartes and if you do not hesitate to share to social science mailng lists.
You are also invited to the post PhD drinks with Monacan specialities that will be held after the defense in Salle Festive (check the map) from 4:30pm and drinks will continue well into the night till 3am.
The members of the jury are:
Director:
– Eric Fleury – ENS de Lyon, INRIA, LIP
Supervisors:
– Crespelle Christophe – UCBL Lyon 1, LIP
– Karsai Marton -ENS de Lyon, INRIA, LIP
Reviewers:
– Magnien Clémence – CNRS, LIP6
– Jari Saramaki – Aalto University
Examiners:
– Cardon Dominique – Science Po Paris, Medialab
– Lambiotte Renaud – University of Namur
Abstract:
In this thesis, I have carried out data-driven studies based on rich, large-scale combined data sets including social links between users (calls and SMS), their demographic parameters (age and gender), their mobility and their economic information such as income and spendings. These seven studies bring insights in network science but also in sociology, economy and geography. The questions asked are very diversified. How can one quantify the loss of temporal information caused by the aggregation of link streams into series of graphs? How can one infer mobility of a user from his or her localisations of calls? Is it possible to transmit SMS in a dense region by using the density of phones, the mobility of users and the locality of the messages? How can one quantify and prove empirically the social stratification of the society at a large population scale? I present, for this last question, a first socio-economic study with a data-driven approach. It has been possible to study, at a very large scale, the stratification of the society, the existence of “rich-clubs”, the spatial segregation and purchase patterns for each social class.
