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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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Dissertation

The Structural Determinants of Media Contagion

TL;DR: Bender et al. as mentioned in this paper studied the role of weblogs in media contagion through a sociological study of this community in two parts: first, they address the issues of modeling the social structure of Weblogs as observed through their readership network, and the various media events that occur therein.
Journal ArticleDOI

Scale invariance in natural and artificial collective systems : a review

TL;DR: This review identifies three main types of self-organized scale-invariant systems: scale- Invariant spatial structures, scale- invariant topologies and scale-Invariant dynamics.
Journal ArticleDOI

Using graph concepts to understand the organization of complex systems

TL;DR: This tutorial demonstrates through illustrative examples, how network measures and models have contributed to the elucidation of the organization of complex systems.
Book ChapterDOI

Social group dynamics in networks

TL;DR: In this article, a new algorithm based on a clique percolation technique was proposed to investigate in detail the time dependence of communities on a large scale and uncover basic relationships of the statistical features of community evolution.
Posted Content

Scalable Online Betweenness Centrality in Evolving Graphs

TL;DR: This paper proposes the first truly scalable and practical framework for computing vertex and edge betweenness centrality of large evolving graphs, incrementally and online.
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.
Journal ArticleDOI

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.
Journal ArticleDOI

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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