DMCA
Small World and Scale Free Properties
BibTeX
@MISC{Zaidi_smallworld,
author = {Faraz Zaidi and Arnaud Sallaberry and Guy Melançon and Faraz Zaidi and Arnaud Sallaberry and Guy Melançon},
title = {Small World and Scale Free Properties},
year = {}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
Abstract: Recent interest in complex networks has catalysed the development of numerous models to help artificially generate and understand these networks. Watts and Strogatz presented a model [37] to explain how the two properties of small world networks, high clustering coefficient and low average path length appear in networks. Barabási and Albert gave a model [1] to explain how networks with power-law degree distribution arise in networks. From these two ground breaking results, many researchers have introduced different models to explain the appearance of networks with small world and scale free properties in the real world. In this paper, we focus on social networks and comparatively study the structure of real world and artificially generated networks. The differences and similarities of different models are highlighted and their shortcomings are identified. Further more, we present a new model which produces networks with both small world and scale free properties which are structurally more similar to real world social networks.
Keyphrases
small world scale free property different model real world complex network high clustering coefficient low average path length barab si real world social network social network small world network recent interest new model numerous model many researcher power-law degree distribution arise
