TY  - RPRT
KW  - Complex system
KW  -  social network
KW  -  attribute matrix
KW  -  Indian Buffet process 
Y1  - 2014/07//
UR  - http://arxiv.org/abs/1407.7729
A1  - Boldi, Paolo
A1  - Crimaldi, Irene
A1  - Monti, Corrado
M1  - technical_report
EP  - 34
ID  - eprints2267
N2  - The quest for a model that is able to explain, describe, analyze and simulate real-world complex networks is of uttermost practical as well as theoretical interest. In this paper we introduce and study a network model that is based on a latent attribute structure: each node is characterized by a number of features and the probability of the existence of an edge between two nodes depends on the features they share. Features are chosen according to a process of Indian-Buffet type but with an additional random "fitness" parameter attached to each node, that determines its ability to transmit its own features to other nodes. As a consequence, a node's connectivity does not depend on its age alone, so also "young" nodes are able to compete and succeed in acquiring links. One of the advantages of our model for the latent bipartite "node-attribute" network is that it depends on few parameters with a straightforward interpretation. We provide some theoretical, as well experimental, results regarding the power-law behaviour of the model and the estimation of the parameters. By experimental data, we also show how the proposed model for the attribute structure naturally captures most local and global properties (e.g., degree distributions, connectivity and distance distributions) real networks exhibit.

TI  - A Network Model characterized by a Latent Attribute Structure with Competition
AV  - none
N1  - preprint arXiv 1407.7729, submitted
ER  -