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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

Temporal betweenness centrality in dynamic graphs

TL;DR: The bi-objective notion of shortest–fastest path (SFP) in temporal graphs is proposed, which considers both space and time as a linear combination governed by a parameter, and a novel temporal betweenness centrality (TBC) metric is defined that outperforms static BC in the task of identifying the best vertices for propagating information.
Journal ArticleDOI

Spread of hospital-acquired infections: A comparison of healthcare networks

TL;DR: Patient transfer patterns at both the French regional and departmental levels that are important in the identification of key hospital centers, patient flow trajectories, and regional clusters that may serve as a basis for novel wide-scale infection control strategies are identified.
Journal ArticleDOI

Modelling collaboration networks based on nonlinear preferential attachment

TL;DR: The proposed model based on nonlinear preferential attachment for collaboration networks can produce the peak act-size distribution naturally that agrees with the empirical data well, and this model exhibits small-world effect, which means the corresponding networks are of very short average distance and highly large clustering coefficient.
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Can World System Theory predict news flow on twitter? The case of government-sponsored broadcasting

TL;DR: This paper examined the unique case of government-sponsored news media and its international news flow and found that non-institutional actors (e.g. bloggers) conformed less than institutional players to that structure.
Proceedings ArticleDOI

Betweenness centrality: algorithms and implementations

TL;DR: A new asynchronous parallel algorithm for betweenness centrality is derived that works seamlessly for both weighted and unweighted graphs, can be applied to large graphs, and is able to extract large amounts of parallelism.
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.
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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.
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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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