Role of Cutoff Scaling in Scale-Free Networks

2018 ◽  
Vol 68 (5) ◽  
pp. 563-569
Author(s):  
Meesoon HA*
Keyword(s):  
Scale Free ◽  
Scale Free Networks

scholarly journals The role of detachment of in-links in scale-free networks

2014 ◽  
Vol 47 (34) ◽  
pp. 345002 ◽  
Author(s):  
P Lansky ◽  
F Polito ◽  
L Sacerdote
Keyword(s):  
Scale Free ◽  
Scale Free Networks

scholarly journals Synchronization in scale-free networks: The role of finite-size effects

2015 ◽  
Vol 110 (6) ◽  
pp. 66001 ◽  
Author(s):  
D. Torres ◽  
M. A. Di Muro ◽  
C. E. La Rocca ◽  
L. A. Braunstein
Keyword(s):  
Size Effects ◽  
Finite Size ◽  
Finite Size Effects ◽  
Scale Free ◽  
Scale Free Networks

scholarly journals MUTUAL SELECTION IN NETWORK EVOLUTION: THE ROLE OF THE INTRINSIC FITNESS

2010 ◽  
Vol 21 (01) ◽  
pp. 129-135 ◽  
Author(s):  
XIN-JIAN XU ◽  
LIU-MING ZHANG ◽  
LI-JIE ZHANG
Keyword(s):  
Distribution Function ◽  
Probability Distribution Function ◽  
Probability Function ◽  
Power Laws ◽  
Network Evolution ◽  
Scale Free ◽  
Scale Free Networks ◽  
Intrinsic Character ◽  
Fitness Distribution

We propose a new mechanism leading to scale-free networks which is based on the presence of an intrinsic character of a vertex called fitness. In our model, a vertex i is assigned a fitness xi, drawn from a given probability distribution function f(x). During network evolution, with rate p we add a vertex j of fitness xj and connect to an existing vertex i of fitness xi selected preferentially to a linking probability function g(xi, xj) which depends on the fitnesses of the two vertices involved and, with rate 1 - p we create an edge between two already existed vertices with fitnesses xi and xj, with a probability also preferential to the connection function g(xi, xj). For the proper choice of g, the resulting networks have generalized power-laws, irrespective of the fitness distribution of vertices.

scholarly journals Not All Scale-Free Networks Are Born Equal: The Role of the Seed Graph in PPI Network Evolution

2007 ◽  
Vol 3 (7) ◽  
pp. e118 ◽  
Author(s):  
Fereydoun Hormozdiari ◽  
Petra Berenbrink ◽  
Nataša Pržulj ◽  
S. Cenk Sahinalp
Keyword(s):  
Network Evolution ◽  
Ppi Network ◽  
Scale Free ◽  
Scale Free Networks

scholarly journals Role of fractal dimension in random walks on scale-free networks

2011 ◽  
Vol 84 (2) ◽  
pp. 331-338 ◽  
Author(s):  
Zhongzhi Zhang ◽  
Yihang Yang ◽  
Shuyang Gao
Keyword(s):  
Fractal Dimension ◽  
Random Walks ◽  
Scale Free ◽  
Scale Free Networks

ROLE OF EDGES IN COMPLEX NETWORK EPIDEMIOLOGY

2012 ◽  
Vol 23 (09) ◽  
pp. 1250059 ◽  
Author(s):  
HAO ZHANG ◽  
ZHI-HONG JIANG ◽  
HUI WANG ◽  
FEI XIE ◽  
CHAO CHEN
Keyword(s):  
Complex Network ◽  
Message Passing ◽  
Configuration Model ◽  
Edge Deletion ◽  
Scale Free ◽  
Large Size ◽  
Network Epidemiology ◽  
Scale Free Networks ◽  
Transmission Capability

In complex network epidemiology, diseases spread along contacting edges between individuals and different edges may play different roles in epidemic outbreaks. Quantifying the efficiency of edges is an important step towards arresting epidemics. In this paper, we study the efficiency of edges in general susceptible-infected-recovered models, and introduce the transmission capability to measure the efficiency of edges. Results show that deleting edges with the highest transmission capability will greatly decrease epidemics on scale-free networks. Basing on the message passing approach, we get exact mathematical solution on configuration model networks with edge deletion in the large size limit.

scholarly journals Dynamics analysis of an online gambling spreading model on scale-free networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yu Kong ◽  
Tao Li ◽  
Yuanmei Wang ◽  
Xinming Cheng ◽  
He Wang ◽  
...  
Keyword(s):  
Network Topology ◽  
Negative Impact ◽  
Online Gambling ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Scale Free ◽  
Spreading Model ◽  
Spreading Dynamics ◽  
Scale Free Networks ◽  
Gambling Policy

AbstractNowadays, online gambling has a great negative impact on the society. In order to study the effect of people’s psychological factors, anti-gambling policy, and social network topology on online gambling dynamics, a new SHGD (susceptible–hesitator–gambler–disclaimer) online gambling spreading model is proposed on scale-free networks. The spreading dynamics of online gambling is studied. The basic reproductive number $R_{0}$ R 0 is got and analyzed. The basic reproductive number $R_{0}$ R 0 is related to anti-gambling policy and the network topology. Then, gambling-free equilibrium $E_{0}$ E 0 and gambling-prevailing equilibrium $E_{ +} $ E + are obtained. The global stability of $E_{0}$ E 0 is analyzed. The global attractivity of $E_{ +} $ E + and the persistence of online gambling phenomenon are studied. Finally, the theoretical results are verified by some simulations.

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