| Abstract 摘要 | Fueled by a wealth of data supplied by a wide range of high-throughput tools and technologies, the study of complex systems is currently
reshaping a number of research fields from social science to computer science and biology. This data-rich reality calls for new approaches and techniques to harvest the hidden information and devise new models to explain the underlying principles of various complex systems. While from a functional standpoint different systems may appear to be distinct from one another, there is an increasing realization that they often share similar structural and dynamic properties. Such similarities offer new perspectives and unique opportunities for physicists to apply their methodologies on a much broader set of phenomena. In this talk, I will first present a macroscopic study of large-scale network structures observed in diverse datasets, and next focus on understanding social activities such as communication and traveling pattern at the each individual level. In the end, I will show a series of relationships that link the quantities characterizing social networks and human dynamics, and demonstrate their generality across a wide range of systems, from mobile calls to tweets. |
