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Counting the number of triangles in a graph has many important applications in network analysis. Several frequently computed metrics like the clustering coefficient and the transitivity ratio need to count the number of triangles in the…

Data Structures and Algorithms · Computer Science 2013-04-24 Mostafa Haghir Chehreghani

Scale-free networks, in which the distribution of the degrees obeys a power-law, are ubiquitous in the study of complex systems. One basic network property that relates to the structure of the links found is the degree assortativity, which…

Physics and Society · Physics 2015-06-22 Oliver Williams , Charo I. Del Genio

We propose a random bipartite graph with weights assigned to both parts of the vertex sets. Edges are formed independently with probabilities that depend on these weights. This bipartite graph naturally gives rise to a random intersection…

Probability · Mathematics 2025-06-10 Alastair Haig , Minmin Wang

We study the properties of random graphs where for each vertex a {\it neighbourhood} has been previously defined. The probability of an edge joining two vertices depends on whether the vertices are neighbours or not, as happens in Small…

Disordered Systems and Neural Networks · Physics 2009-11-10 Sebastian Risau-Gusman

High triangle density -- the graph property stating that a constant fraction of two-hop paths belong to a triangle -- is a common signature of social networks. This paper studies triangle-dense graphs from a structural perspective. We prove…

Data Structures and Algorithms · Computer Science 2014-02-10 Rishi Gupta , Tim Roughgarden , C. Seshadhri

A fundamental property of complex networks is the tendency for edges to cluster. The extent of the clustering is typically quantified by the clustering coefficient, which is the probability that a length-2 path is closed, i.e., induces a…

Social and Information Networks · Computer Science 2018-05-23 Hao Yin , Austin R. Benson , Jure Leskovec

For $n\geq 3$, let $r=r(n)\geq 3$ be an integer. A hypergraph is $r$-uniform if each edge is a set of $r$ vertices, and is said to be linear if two edges intersect in at most one vertex. In this paper, the number of linear $r$-uniform…

Combinatorics · Mathematics 2019-08-20 Brendan D. McKay , Fang Tian

Graphs are used to model interactions in a variety of contexts, and there is a growing need to quickly assess the structure of such graphs. Some of the most useful graph metrics are based on triangles, such as those measuring social…

Social and Information Networks · Computer Science 2014-10-21 C. Seshadhri , Ali Pinar , Tamara G. Kolda

We consider the edge-triangle model, a two-parameter family of exponential random graphs in which dependence between edges is introduced through triangles. In the so-called replica symmetric regime, the limiting free energy exists together…

Probability · Mathematics 2023-01-31 Alessandra Bianchi , Francesca Collet , Elena Magnanini

Real-world networks, e.g. the social relations or world-wide-web graphs, exhibit both small-world and scale-free behaviour. We interpret lattice triangulations as planar graphs by identifying triangulation vertices with graph nodes and…

Disordered Systems and Neural Networks · Physics 2015-02-06 Benedikt Krüger , Ella M. Schmidt , Klaus Mecke

We consider the set of all graphs on n labeled vertices with prescribed degrees D=(d_1, ..., d_n). For a wide class of tame degree sequences D we prove a computationally efficient asymptotic formula approximating the number of graphs within…

Combinatorics · Mathematics 2011-12-05 Alexander Barvinok , J. A. Hartigan

We find the asymptotic number of connected graphs with $k$ vertices and $k-1+l$ edges when $k,l$ approach infinity, reproving a result of Bender, Canfield and McKay. We use the {\em probabilistic method}, analyzing breadth-first search on…

Combinatorics · Mathematics 2007-05-23 Remco van der Hofstad , Joel Spencer

We study the properties of the giant connected component in random graphs with arbitrary degree distribution. We concentrate on the degree-degree correlations. We show that the adjoining nodes in the giant connected component are correlated…

Statistical Mechanics · Physics 2010-05-11 Piotr Bialas , Andrzej K. Oleś

We propose a simple random process inducing various types of random graphs and the scale free random graphs among others. The model is of a threshold nature and differs from the preferential attachment approach discussed in the literature…

Disordered Systems and Neural Networks · Physics 2007-05-23 D. Volchenkov , Ph. Blanchard

The global clustering coefficient is an effective measure for analyzing and comparing the structures of complex networks. The random annulus graph is a modified version of the well-known Erd\H{o}s-R\'{e}nyi random graph. It has been…

Methodology · Statistics 2025-10-20 Mingao Yuan

We give an asymptotic expression for the expected number of spanning trees in a random graph with a given degree sequence $\boldsymbol{d}=(d_1,\ldots, d_n)$, provided that the number of edges is at least $n + \textstyle{\frac{1}{2}}…

Combinatorics · Mathematics 2017-02-21 Catherine Greenhill , Mikhail Isaev , Matthew Kwan , Brendan D. McKay

We provide large deviations estimates for the upper tail of the number of triangles in scale-free inhomogeneous random graphs where the degrees have power law tails with index $-\alpha, \alpha \in (1,2)$. We show that upper tail…

Probability · Mathematics 2024-03-25 Clara Stegehuis , Bert Zwart

We analyse graphs in which each vertex is assigned random coordinates in a geometric space of arbitrary dimensionality and only edges between adjacent points are present. The critical connectivity is found numerically by examining the size…

Statistical Mechanics · Physics 2009-11-07 Jesper Dall , Michael Christensen

We extend the classical preferential attachment random graph model to random simplicial complexes. At each stage of the model, we choose one of the existing $k$-simplices with probability proportional to its $k$-degree. The chosen…

Probability · Mathematics 2024-10-24 Takashi Owada , Gennady Samorodnitsky

In this paper, a random clique network model to mimic the large clustering coefficient and the modular structure that exist in many real complex networks, such as social networks, artificial networks, and protein interaction networks, is…

Physics and Society · Physics 2017-05-05 Yi-Min Ding , Jun Meng , Jing-Fang Fan , Fang-Fu Ye , Xiao-Song Chen
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