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Human behavior through dynamics of complex social networks: an interdisciplinary approach

Objective

This project aims to further develop the basic science of complex social networks in a quantitative way, and apply our findings to the dynamics of human behavior. We intend to generalize and apply our results to a wider range of networks, including economi c, traffic, and environmental networks, thus establishing an interdisciplinary program of research based in complex social networks. Thus, the methods and techniques to be developed, based on Statistical Physics concepts, will be of further use in a variet y of other fields. To date, the application of complexity to the topology and emergent dynamic behavior in social networks has been mostly limited, qualitative, and rather empirical. We propose to use quantitative characterization of complex social network s by analyzing a number of real-world phenomena, including: crowd behavior, search strategies, traffic flow, dynamics of human relationship networks, spread of epidemics, as well as dynamic patterns in other disciplines, such as Economics and Finance, and Environmental networks. A principal goal is to characterize, optimize and control the structure, dynamics and flow in complex social networks, aiming to uncover the organizing principles that limit and influence the emergence of collective behavior in such systems. This work will also test the hypothesis that the dynamics of certain collective human behavior is governed by an underlying drive to optimize certain aspects of the underlying network on which this behavior takes place. Our studies will use exten sive real-world data of social nature, which will be collected in the frame of the project. The consortium will bring together scientists of various disciplines working in the emerging field of complex networks, in order to study topology and dynamics of s ocial networks at a large scale. Our study will enable to develop useful applications, e.g. approaches for efficient optimisation, control panic and optimize searching of lost people, etc.

Call for proposal

FP6-2003-NEST-PATH
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Funding Scheme

STREP - Specific Targeted Research Project

Coordinator

ARISTOTLE UNIVERSITY OF THESSALONIKI
Address
Administration Building, University Campus
Thessaloniki
Greece

Participants (6)

BAR ILAN UNIVERSITY
Israel
Address
Bar-ilan University
Ramat Gan
ISTITUTO NAZIONALE PER LA FISICA DELLA MATERIA
Italy
Address
Corso Perrone 24
Genova
JUSTUS-LIEBIG-UNIVERSITAET GIESSEN
Germany
Address
Ludwigstrasse 23
Giessen
STOCKHOLMS UNIVERSITET
Sweden
Address
Universitetsvägen 10
Stockholm
TRUSTEES OF BOSTON UNIVERSITY
United States
Address
881 Commonwealth Avenue
Boston, Ma
UNIVERSIDADE DE AVEIRO
Portugal
Address
Campus Universitario De Santiago
Aveiro