Due to its wide reaching implications for everything from identifying hot spots of income
inequality to political redistricting, there is a rich body of literature across the sciences …

We examine the structure of the percolating cluster (PC) formed by site percolation on a
random clustered network (RCN) model. Using the generating functions, we formulate the …

In this work, we explore degree assortativity in complex networks, and extend its usual
definition beyond that of nearest neighbours. We apply this definition to model networks, and …

Correlations among the degrees of vertices in random graphs often occur when clustering is
present. In this paper we define a joint-degree correlation function for vertices in the giant …

Correlation of words in the text is of great importance in text analysis like text retrieval,
keywords extraction, and text clustering. For short text, because of the limited information of …

We perform an analysis of the long-range degree correlation of the giant component (GC) in
an uncorrelated random network by employing generating functions. By introducing a …

The presence of large-scale real-world networks with various architectures has motivated
active research towards a unified understanding of diverse topologies of networks. Such …

Exponential random graphs are important to model the structure of real-world complex
networks. Here we solve the two-star model with degree-degree correlations in the sparse …

In this paper, we consider the friendship paradox in the context of random walks and paths.
Among our results, we give an equality connecting long-range degree correlation, degree …

Existing studies on the degree correlation of evolving networks typically rely on differential
equations and statistical analysis, resulting in only approximate solutions due to inherent …