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Open AccessJournal ArticleDOI

The Web of Human Sexual Contacts

TLDR
In this article, the authors analyze data on the sexual behavior of a random sample of individuals, and find that the cumulative distributions of the number of sexual partners during the twelve months prior to the survey decays as a power law with similar exponents for females and males.
Abstract
Many ``real-world'' networks are clearly defined while most ``social'' networks are to some extent subjective. Indeed, the accuracy of empirically-determined social networks is a question of some concern because individuals may have distinct perceptions of what constitutes a social link. One unambiguous type of connection is sexual contact. Here we analyze data on the sexual behavior of a random sample of individuals, and find that the cumulative distributions of the number of sexual partners during the twelve months prior to the survey decays as a power law with similar exponents $\alpha \approx 2.4$ for females and males. The scale-free nature of the web of human sexual contacts suggests that strategic interventions aimed at preventing the spread of sexually-transmitted diseases may be the most efficient approach.

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Citations
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Journal ArticleDOI

The SIRS Model of Epidemic Spreading in Virtual Society

TL;DR: It was found that the activity of an individual is positively correlated with its connectivity and the relation has power law form and the form of activity distribution has signiflcant effect on the spreading phenomena in the network.
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Correction for Volz and Meyers, Susceptible-infected-recovered epidemics in dynamic contact networks

TL;DR: Correction for ‘Susceptible-infected-recovered epidemics in dynamic contact networks’ by Erik Volz and Lauren Ancel Meyers (Proc. R. Soc. B 274, 2925–2933).
Journal ArticleDOI

Statistical study of characteristics of online reading behavior networks in university digital library

TL;DR: It is revealed that the degree distribution of an online reading behavior network obeys the exponential distribution and the small-world phenomenon is observed in ORBNs.

Contrasting within- and between-host immune selection shapes Neisseria Opa

TL;DR: In this article, the authors use a simple mathematical model and genomic data to show that trade-offs between immune selection pressures within and between hosts can explain the contrasting Opa repertoires observed in meningococci and gonococci.
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Connectedness matters: construction and exact random sampling of connected networks

Sz Horvát, +1 more
TL;DR: A new method for the random sampling of connected networks with a specified degree sequence is described, which builds on a recently introduced novel sampling approach that constructs graphs with given degrees independently and efficiently and extends it to incorporate the constraint of connectedness.
References
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Journal ArticleDOI

Collective dynamics of small-world networks

TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
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Emergence of Scaling in Random Networks

TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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Statistical mechanics of complex networks

TL;DR: In this paper, a simple model based on the power-law degree distribution of real networks was proposed, which was able to reproduce the power law degree distribution in real networks and to capture the evolution of networks, not just their static topology.
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The Structure and Function of Complex Networks

Mark Newman
- 01 Jan 2003 - 
TL;DR: Developments in this field are reviewed, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
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Complex networks: Structure and dynamics

TL;DR: The major concepts and results recently achieved in the study of the structure and dynamics of complex networks are reviewed, and the relevant applications of these ideas in many different disciplines are summarized, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.
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