Digital traces of human mobility and interaction: models and applications

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

Topology Reconstruction of Dynamical Networks via Constrained Lyapunov Equations

The network structure (or topology) of a dynamical network is often unavailable or uncertain. Hence, we consider the problem of network reconstruction. Network reconstruction aims at inferring the topology of a dynamical network using measurements obtained from the network. In this technical note we define the notion of solvability of the network reconstruction problem. Subsequently, we provide necessary and sufficient conditions under which the network reconstruction problem is solvable. Finally, using constrained Lyapunov equations, we establish novel network reconstruction algorithms, applicable to general dynamical networks. We also provide specialized algorithms for specific network dynamics, such as the well-known consensus and adjacency dynamics.Comment: 8 page

Advances in Computational Social Science and Social Simulation

Aquesta conferència és la celebració conjunta de la "10th Artificial Economics Conference AE", la "10th Conference of the European Social Simulation Association ESSA" i la "1st Simulating the Past to Understand Human History SPUHH".Conferència organitzada pel Laboratory for Socio­-Historical Dynamics Simulation (LSDS-­UAB) de la Universitat Autònoma de Barcelona.Readers will find results of recent research on computational social science and social simulation economics, management, sociology,and history written by leading experts in the field. SOCIAL SIMULATION (former ESSA) conferences constitute annual events which serve as an international platform for the exchange of ideas and discussion of cutting edge research in the field of social simulations, both from the theoretical as well as applied perspective, and the 2014 edition benefits from the cross-fertilization of three different research communities into one single event. The volume consists of 122 articles, corresponding to most of the contributions to the conferences, in three different formats: short abstracts (presentation of work-in-progress research), posters (presentation of models and results), and full papers (presentation of social simulation research including results and discussion). The compilation is completed with indexing lists to help finding articles by title, author and thematic content. We are convinced that this book will serve interested readers as a useful compendium which presents in a nutshell the most recent advances at the frontiers of computational social sciences and social simulation researc