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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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Information horizons in a complex world

TL;DR: The whole in a complex system is the sum of its parts, plus the interactions between the parts as mentioned in this paper, and understanding social, biological, and economic systems therefore often depends on understanding their interactions.
Journal ArticleDOI

Pathogen spread on coupled networks: effect of host and network properties on transmission thresholds.

TL;DR: This work extends existing network theory to find the effect of multiple networks and multiple host types on epidemic thresholds and applies the results to the example of HIV and TB to illustrate how the interactions of the diseases can substantially alter the epidemic threshold of TB.
Journal ArticleDOI

Gaining scale-free and high clustering complex networks

TL;DR: It is shown that the given model can successfully capture two generic topological properties of many real networks: they are scale-free and they display a high degree of clustering.
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A characterization of internet dating network structures among nordic men who have sex with men.

TL;DR: The flirt network showed high degree heterogeneity similar to the structural properties of real sexual contact networks with a single central core, and possession of a webcam was strongly associated with both sending flirt messages and being a flirt target.
Proceedings ArticleDOI

Complex Innovation Networks, Patent Citations and Power Laws

TL;DR: It is demonstrated that the citation network is a scale free network and the network node degree probability distribution follows a power law, meaning the probability that a patent is highly connected to other patents is statistically more likely than would be expected via random connections and associations.
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.
Journal ArticleDOI

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.
Journal ArticleDOI

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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