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arXiv · 1803.00263

EvoCut : A new Generalization of Albert-Barabási Model for Evolution of Complex Networks

Shailesh Kumar Jaiswal·Nabajyoti Medhi·Manjish Pal·Mridul Sahu·Prashant Sahu·Amal Dev Sarma
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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 Barabási-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.

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Shailesh Kumar Jaiswal, Nabajyoti Medhi, Manjish Pal, Mridul Sahu, Prashant Sahu, Amal Dev Sarma. 2018-03-01. EvoCut : A new Generalization of Albert-Barabási Model for Evolution of Complex Networks. https://arxiv.org/abs/1803.00263

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