English

Influence of reciprocal arcs on the degree distribution and degree correlations

Statistical Mechanics 2011-05-23 v1 Disordered Systems and Neural Networks Data Analysis, Statistics and Probability

Abstract

Reciprocal arcs represent the lowest order cycle possible to find in directed graphs without self-loops. Representing also a measure of feed-back between vertices, it is interesting to understand how reciprocal arcs influence other properties of complex networks. In this paper we focus on influence of reciprocal arcs on vertex degree distribution and degree correlations. We show that there is a fundamental difference between properties observed on the static network compared to the properties of networks which are obtained by simple evolution mechanism driven by reciprocity. We also present a way to statistically infer the portion of reciprocal arcs which can be explained as a consequence of feed-back process on the static network. In the rest of the paper the influence of reciprocal arcs on a model of growing network is also presented. It is shown that our model of growing network nicely interpolates between BA model for undirected and the BA model for directed networks.

Keywords

Cite

@article{arxiv.0902.3542,
  title  = {Influence of reciprocal arcs on the degree distribution and degree correlations},
  author = {Vinko Zlatić and Hrvoje Štefančić},
  journal= {arXiv preprint arXiv:0902.3542},
  year   = {2011}
}

Comments

13 pages, 11 figures, companion paper of our paper: "Model of Wikipedia growth based on information exchange via reciprocal arcs"