Editorial: At the Crossroads: Lessons and Challenges in Computational Social Science

The interest of physicists in economic and social questions is not new: during the last decades, we have witnessed the emergence of what is formally called nowadays sociophysics [1] and econophysics [2] that can be grouped into the common term “Interdisciplinary Physics” along with biophysics, medical physics, agrophysics, etc. With tools borrowed from statistical physics and complexity science, among others, these areas of study have already made important contributions to our understanding of how humans organize and interact in our modern society. Large scale data analyses, agent-based modeling and numerical simulations, and finally mathematical modeling, have led to the discovery of new (universal) patterns and their quantitative description in socio-economic systems. At the turn of the century, however, it was clear that huge challenges—and new opportunities— lied ahead: the digital communication technologies, and their associated data deluge, began to nurture those models with empirical significance. Only a decade later, the advent of the Web 2.0, the Internet of Things and a general adoption of mobile technologies have convinced researchers that theories can be mapped to real scenarios and put into empirical test, closing in this way the experiment-theory cycle in the best tradition of physics

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Published in: Frontiers in Physics
License: https://creativecommons.org/licenses/by/4.0/  
See article on publisher's website: https://dx.doi.org/10.3389/fphy.2016.00037