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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 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.
Journal ArticleDOI

Statistical physics of social dynamics

TL;DR: In this article, a wide list of topics ranging from opinion and cultural and language dynamics to crowd behavior, hierarchy formation, human dynamics, and social spreading are reviewed and connections between these problems and other, more traditional, topics of statistical physics are highlighted.
Journal ArticleDOI

Evolution of networks

TL;DR: The recent rapid progress in the statistical physics of evolving networks is reviewed, and how growing networks self-organize into scale-free structures is discussed, and the role of the mechanism of preferential linking is investigated.
Journal ArticleDOI

Epidemic processes in complex networks

TL;DR: A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear.
References
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Journal ArticleDOI

Social Network Analysis Predicts Health Behaviours and Self-Reported Health in African Villages

TL;DR: In-degree and betweenness independently explained self-reported health and behaviour, respectively, and the results suggest that targeting households based on network measures rather than health status may be effective for promoting the uptake of health interventions in rural poor villages.
Journal ArticleDOI

A signalling explanation for preferential attachment in the evolution of social networks

TL;DR: In this article, the authors provide several models that overcome the three drawbacks of the network theory developed by physicists and explain preferential attachment as rational equilibrium behavior, and argue that a person has an incentive to form a link with another who has many links because the number of his links can convey some information about his value.
Journal ArticleDOI

Step-by-Step Random Walk Network with Power-Law Clique-Degree Distribution ⁄

TL;DR: It is found that the clique-degree distribution based on the model obeys a power-law form, which is in agreement with the recently empirical evidences.
Book ChapterDOI

Social Network of Co-occurrence in News Articles

TL;DR: Results reveal that like the previously studied social networks the social network of co-occurrence in news articles also possesses the small-world and power-law degree distribution properties.
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