The Complex Systems group at IN3 (CoSIN3) develops research towards the discovery of underlying mechanisms in complex networked systems. Such research comes both with a fundamental and an applied emphasis, pivoting mostly (but not exclusively) on two pillars: 

- Computational Social Science (CSS), lying at the a crossroads to which different approaches converge: CSS is a new discipline that can offer powerful models and methods (mainly from Complex Systems), large datasets, algorithms and computational power (Computer and Data Science), and a conceptual framework for the results to be interpreted (Social Science).

At CoSIN3 we pursue the following research problems:

1- Temporal and geographical patterns of online information diffusion: collective attention modeling, tracking and forecasting. Exogenous vs. endogenous events.

2- Information ecosystems and user-information interplay: detect, quantify and understand the competitive/cooperative dynamics in temporally evolving, information-driven systems.

3- Social simulation, cultural and opinion dynamics: exploit the sociophysics approach to uncover social dynamics mechanisms; close the theory-experiment cycle through empirical calibration and validation of agent-based social models

Urban Science: a city is a set of interwoven layers of personal interaction, infrastructural networks (communication, transportation, energy), land use, air quality, etc. As such, its emergent behaviors cannot be described by simple aggregation of the behavior of the parts. Understanding the city system and the relationships between its parts creates interdisciplinary opportunities and challenges, gathering policy decision makers, landscape and urban planning, data science, multiplex network science and social sciences.

More information: cosin3.rdi.uoc.edu.