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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

All Scale-free networks are sparse

TL;DR: The realizability of scale-free networks with a given degree sequence is studied, showing that the fraction of realizable sequences undergoes two first-order transitions at the values 0 and 2 of the power-law exponent.
Proceedings ArticleDOI

A faster parallel algorithm and efficient multithreaded implementations for evaluating betweenness centrality on massive datasets

TL;DR: A new lock-free parallel algorithm for computing betweenness centrality of massive complex networks that achieves better spatial locality compared with previous approaches is presented, and the applicability of this implementation to analyze massive real-world datasets is demonstrated.
Proceedings ArticleDOI

Massive Social Network Analysis: Mining Twitter for Social Good

TL;DR: This work presents GraphCT, a Graph Characterization Toolkit for massive graphs representing social network data, and uses GraphCT to analyze public data from Twitter, a microblogging network.
Journal ArticleDOI

The Social Origins of Networks and Diffusion.

TL;DR: The author develops a model of social network formation that explores how social and structural constraints on tie formation generate emergent social topologies and explores the effectiveness of these social networks for the dynamics of social diffusion, and finds that successful social diffusion can depend on moderate to high levels of structural consolidation.
Journal ArticleDOI

The cell graphs of cancer

TL;DR: It is demonstrated that the self-organizing clusters of cancerous cells exhibit distinctive graph metrics that distinguish them from the healthy cells and the unhealthy inflamed cells at the cellular level with an accuracy of at least 85%.
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