Patterns in Complex Networks via Spectral Analysis
published: Sept. 13, 2010, recorded: August 2010, views: 926
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Complex networks represent a variety of real-world systems in biology, ecology, society and technology. The study of structural properties of such systems has a tremendous impact in our understanding of their function, organisation and dynamics. Here I present a series of results toward the structural characterisation of complex networks. I start by analysing the centrality of nodes in complex networks and we introduce a measure which accounts for the participation of a node in all subgraphs in the network. This method is used to obtain a universal classification of networks into four topological classes. Then, I will develop a method to characterise the communicability between nodes in a network. The method is illustrated by ranking webpages in WWW and it is compared to other algorithms such as PageRank, SALSA, etc. Using the communicability approach I develop a method to identify overlapped communities in networks. I finalise by extending these ideas to account for general matrix functions.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !