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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

Lightweight Centrality Measures in Networks under Attack

TL;DR: It is shown that with the aid of scale-free network characteristics such as the clustering coefficient the authors can get results that balance the current centrality measures, but also gain insight into the workings of these networks.
Journal ArticleDOI

Social network influence and market instability

TL;DR: In this article, the authors studied price stability of a capital market, where the dynamics of participants' opinion formations is formalized using social network models and found that factors of highly connected networks and balanced weight allocation on information sources can in fact be stabilizing.
Proceedings ArticleDOI

Fast Execution of Simultaneous Breadth-First Searches on Sparse Graphs

TL;DR: This paper presents multi-search, a simple abstraction that is designed for graph algorithms requiring many breadth-first searches that can be executed simultaneously, and provides an explicit, reusable implementation that efficiently maps this abstraction to the GPU, performing more than twice as fast as previous approaches on large graphs of varying diameter.
Journal ArticleDOI

Complex network analysis of climate change in the Tarim River Basin, Northwest China

TL;DR: The results show that TFN and PEN both present characteristics of scale-free network and small-world network with short average path length and high clustering coefficient, which indicates that climate change modes represented by these nodes have large probability of occurrence.
Journal ArticleDOI

Scale-free networks with tunable degree-distribution exponents.

TL;DR: A model of scale-free growing networks that gives a degree distribution dominated by a power-law behavior with a model-dependent, hence tunable, exponent is proposed and found to be in good agreement with results obtained by extensive numerical simulations.
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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