TY  - JOUR
IS  - 2
JF  - Interdisciplinary Information Sciences
Y1  - 2017///
SP  - 127
PB  - Tohoku University. Graduate School of Information Sciences
A1  - Crimaldi, Irene
A1  - Del Vicario, Michela
A1  - Morrison, Greg
A1  - Quattrociocchi, Walter
A1  - Riccaboni, Massimo
VL  - 23
UR  - https://www.is.tohoku.ac.jp/en/iis/
KW  - probabilistic modeling
KW  -  complex network
KW  -  assortativity
KW  -  preferential attachment
KW  -  triadic closure.
AV  - none
TI  - Modeling networks with a growing feature-structure
N2  - We present a new network model accounting for multidimensional assortativity. Each node is characterized by a number of features and the probability of a link between two nodes depends on common features. We do not fix a priori the total number of possible features. The bipartite network of the nodes and the features evolves according to a stochastic dynamics that depends on
three parameters that respectively regulate the preferential attachment in the transmission of the features to the nodes, the number of new features per node, and the power-law behavior of the total number of observed features.
Our model also takes into account a mechanism of triadic closure. We provide theoretical results and statistical estimators for the parameters of the model.
We validate our approach by means of simulations and an empirical analysis of a network of scientific collaborations.
SN  - 1340-9050
EP  - 144
ID  - eprints3700
ER  -