EvoCut : A new Generalization of Albert-Barab\'asi Model for Evolution of Complex Networks
Abstract
With the evolution of social networks, the network structure shows dynamic nature in which nodes and edges appear as well as disappear for various reasons. The role of a node in the network is presented as the number of interactions it has with the other nodes. For this purpose a network is modeled as a graph where nodes represent network members and edges represent a relationship among them. Several models for evolution of social networks has been proposed till date, most widely accepted being the Barab\'asi-Albert \cite{Network science} model that is based on \emph{preferential attachment} of nodes according to the degree distribution. This model leads to generation of graphs that are called \emph{Scale Free} and the degree distribution of such graphs follow the \emph{power law}. Several generalizations of this model has also been proposed. In this paper we present a new generalization of the model and attempt to bring out its implications in real life.
Keywords
Cite
@article{arxiv.1803.00263,
title = {EvoCut : A new Generalization of Albert-Barab\'asi Model for Evolution of Complex Networks},
author = {Shailesh Kumar Jaiswal and Nabajyoti Medhi and Manjish Pal and Mridul Sahu and Prashant Sahu and Amal Dev Sarma},
journal= {arXiv preprint arXiv:1803.00263},
year = {2018}
}