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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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Pricing in Social Networks under Limited Information

TL;DR: In this article, the authors model the strategy of a monopolist that offers rewards to current clients in order to induce them to activate their social network and convince peers to buy from the company.
Journal ArticleDOI

Identification of suicide-related events through network analysis of adverse event reports.

TL;DR: The network analysis appears to be a promising method for identifying signals of suicide by analyzing data obtained from the US Food and Drug Administration Adverse Event Reporting System of selective serotonin reuptake inhibitors.
Book ChapterDOI

How Behaviour and the Environment Influence Transmission in Mobile Groups

TL;DR: An agent-based model is used to study how the movement of individuals and characteristics of the signal being transmitted modulate transmission and offers a means by which multi-agent systems can be engineered to achieve desired transmission capabilities.
Posted Content

SIR dynamics in structured populations with heterogeneous connectivity

TL;DR: A system of nonlinear differential equations is presented which describes the behavior of epidemics spreading through random networks with arbitrary degree distributions, and the degree distribution is observed to have significant impact on both the final size and time scale of epidemic.
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