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We investigate the higher-order connectivity of scale-free networks using algebraic topology. We model scale-free networks as preferential attachment graphs, and we study the algebraic-topological properties of their clique complexes. We…

Algebraic Topology · Mathematics 2025-02-25 Chunyin Siu

Suppose in a graph $G$ vertices can be either red or blue. Let $k$ be odd. At each time step, each vertex $v$ in $G$ polls $k$ random neighbours and takes the majority colour. If it doesn't have $k$ neighbours, it simply polls all of them,…

Probability · Mathematics 2015-07-27 Mohammed Amin Abdullah , Michel Bode , Nikolaos Fountoulakis

We deal with a random graph model where at each step, a vertex is chosen uniformly at random, and it is either duplicated or its edges are deleted. Duplication has a given probability. We analyse the limit distribution of the degree of a…

Probability · Mathematics 2014-09-19 Ágnes Backhausz , Tamás F. Móri

We study the following paradox associated with networks growing according to superlinear preferential attachment: superlinear preference cannot produce scale-free networks in the thermodynamic limit, but there are superlinearly growing…

Statistical Mechanics · Physics 2008-08-23 Paul Krapivsky , Dmitri Krioukov

This Master's thesis examines the properties of large degree vertices in random recursive directed acyclic graphs (RRDAGs), a generalization of the well-studied random recursive tree (RRT) model. Using a novel adaptation of Kingman's…

Probability · Mathematics 2025-03-11 Rafael Engel

We consider the open problem concerning the possible lack of concentration of the degree distribution in preferential attachment graphs with random initial degree, when its distribution is characterized by extremely heavy tails of power-law…

Probability · Mathematics 2025-01-30 T. Makai , F. Polito , L. Sacerdote

Selectional preference learning methods have usually focused on word-to-class relations, e.g., a verb selects as its subject a given nominal class. This paper extends previous statistical models to class-to-class preferences, and presents a…

Computation and Language · Computer Science 2007-05-23 Eneko Agirre , David Martinez

Prediction and control of network dynamics are grand-challenge problems in network science. The lack of understanding of fundamental laws driving the dynamics of networks is among the reasons why many practical problems of great…

Physics and Society · Physics 2016-02-02 Konstantin Zuev , Fragkiskos Papadopoulos , Dmitri Krioukov

In this paper we focus on the problem of the degree sequence for the following random graph process. At any time-step $t$, one of the following three substeps is executed: with probability $\alpha_1$, a new vertex $x_t$ and $m$ edges…

Probability · Mathematics 2008-07-01 Xian-Yuan Wu , Zhao Dong , Ke Liu , Kai-Yuan Cai

Preferential attachment is a popular generative mechanism to explain the widespread observation of power law distributed networks. We introduce an alternative explanation for the phenomenon by allowing the link growth rates to vary across…

Physics and Society · Physics 2007-06-18 Birgitte Freiesleben de Blasio , Odd O Aalen

The linear preferential attachment hypothesis has been shown to be quite successful to explain the existence of networks with power-law degree distributions. It is then quite important to determine if this mechanism is the consequence of a…

Statistical Mechanics · Physics 2009-11-07 Alexei Vazquez

The multiplex network growth literature has been confined to homogeneous growth hitherto, where the number of links that each new incoming node establishes is the same across layers. This paper focuses on heterogeneous growth. We first…

Physics and Society · Physics 2015-06-23 Babak Fotouhi , Naghmeh Momeni

Preferential attachment models were shown to be very effective in predicting such important properties of real-world networks as the power-law degree distribution, small diameter, etc. Many different models are based on the idea of…

Probability · Mathematics 2015-12-23 Liudmila Ostroumova Prokhorenkova , Egor Samosvat

Edge expansion is a parameter indicating how well-connected a graph is. It is useful for designing robust networks, analysing random walks or information flow through a network and is an important notion in theoretical computer science.…

Probability · Mathematics 2026-01-12 Colin McDiarmid , Katarzyna Rybarczyk , Fiona Skerman , Małgorzata Sulkowska

Numerous works have been proposed to generate random graphs preserving the same properties as real-life large scale networks. However, many real networks are better represented by hypergraphs. Few models for generating random hypergraphs…

Social and Information Networks · Computer Science 2021-03-03 Frédéric Giroire , Nicolas Nisse , Thibaud Trolliet , Małgorzata Sulkowska

Preferential attachment networks are a type of random network where new nodes are connected to existing ones at random, and are more likely to connect to those that already have many connections. We investigate further a family of models…

Probability · Mathematics 2021-07-28 Ben Andrews , Jonathan Jordan

We model a social-encounter network where linked nodes match for reproduction in a manner depending probabilistically on each node`s attractiveness. The developed model reveals that increasing either the network`s mean degree or the…

Physics and Society · Physics 2017-06-22 S. Dipple , T. Jia , T. Caraco , G. Korniss , B. K. Szymanski

Generalized preferential attachment is defined as the tendency of a vertex to acquire new links in the future with respect to a particular vertex property. Understanding which properties influence link acquisition tendency (LAT) gives us a…

Adaptation and Self-Organizing Systems · Physics 2011-11-09 Amac Herdagdelen , Eser Aygun , Haluk Bingol

We study the standard SIS model of epidemic spreading on networks where individuals have a fluctuating number of connections around a preferred degree $\kappa $. Using very simple rules for forming such preferred degree networks, we find…

Statistical Mechanics · Physics 2012-12-05 Shivakumar Jolad , Wenjia Liu , B. Schmittmann , R. K. P. Zia

We study properties of some standard network models when the population is split into two types and the connection pattern between the types is varied. The studied models are generalizations of the Erd\H{o}s-R\'{e}nyi graph, the…

Probability · Mathematics 2017-07-17 Maria Deijfen , Robert Fitzner
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