TY - JOUR
T1 - Activity ageing in growing networks
AU - Lambiotte, R.
N1 - Copyright 2007 Elsevier B.V., All rights reserved.
PY - 2007/2/1
Y1 - 2007/2/1
N2 - We present a model for growing information networks where the ageing of a node depends on the time at which it entered the network and on the last time it was cited. The model is shown to undergo a transition from a small-world to a large-world network. The degree distribution may exhibit very different shapes depending on the model parameters, e.g.delta-peaked, exponential or power-law tailed distributions.
AB - We present a model for growing information networks where the ageing of a node depends on the time at which it entered the network and on the last time it was cited. The model is shown to undergo a transition from a small-world to a large-world network. The degree distribution may exhibit very different shapes depending on the model parameters, e.g.delta-peaked, exponential or power-law tailed distributions.
UR - http://www.scopus.com/inward/record.url?scp=42749100726&partnerID=8YFLogxK
U2 - 10.1088/1742-5468/2007/02/P02020
DO - 10.1088/1742-5468/2007/02/P02020
M3 - Article
AN - SCOPUS:42749100726
SN - 1742-5468
JO - Journal of Statistical Mechanics: Theory and Experiment
JF - Journal of Statistical Mechanics: Theory and Experiment
IS - 2
ER -