University of California Multi-Campus Complexity Events 2011-2012 VTCs continue in a new format

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UCSD Complex Network Seminar special meeting, Thursday, August, 25, 2011

Subject:  	Talk by Dashun Wang: UCSD Complex Network Seminar special meeting, Thursday, August, 25, 2011
From:  	"Maksim Kitsak" <> 
To:  	"Maksim Kitsak" <> (more)

Dear Colleagues,

I would like to announce a talk by Dashun Wang, Center for Complex Network Research (CCNR), Northeastern University.

Date: Aug. 25, 2011 Place: SDSC room 408 (Central Building) Time: 13.00 p.m.

Title: Human Mobility and Social Networks

Abstract: Our understanding of how individual mobility patterns shape and impact the social network is limited, but is essential for a deeper understanding of the organization of society as a whole. This question is largely unexplored, partly due to the difficulty in obtaining large-scale society-wide data that simultaneously capture the dynamical information on individual movements and social interactions. Here we address this challenge by tracking the trajectories and communication records of 6 Million mobile phone users. We find that the similarity between two individuals' movements strongly correlates with their proximity in the social network. We further show that individual mobility could indeed serve as a good predictor of the structure of the network, and spatial co-location strongly impacts the organization of social network. We believe our findings on the interplay of individual mobility patterns and social network provide significant insights towards a deeper understanding of not only human dynamics but also network evolution.

Hope to see all of you at the seminar!

Best regards, Maksim Kitsak P.S. More info on how to get to SDSC is at

HSC Videoconference Friday May 27 2011 Maksim Kitsak

Maksim Kitsak - Cooperative Association for Internet Data Analysis (CAIDA) in SDSC at UCSD - =

Title: Do bipartite networks have metric structure? Flyer for talk

Abstract: Many social, biological and technological systems can be conveniently represented as bipartite networks, consisting of two disjoint sets of elements along with edges connecting only elements from different sets. Many of such systems are characterized by high values of bipartite clustering coefficient. We also find that pairs of elements in these bipartite systems tend to have many common neighbors. We present a natural interpretation of these observations. We suggest that elements of the above bipartite systems exist in underlying metric spaces, such that the observed high clustering is a topological reflection of the triangle inequality, the key property of metric space. We propose a simple stochastic mechanism of formation of bipartite networks embedded in metric spaces. We prove that this mechanism is able to reproduce the observed topological properties of bipartite networks. We also discuss the possibility of constructive embedding of real bipartite systems into metric spaces.