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.read more
Citations
More filters
Journal ArticleDOI
Networking the seceder model: Group formation in social and economic systems.
Andreas Grönlund,Petter Holme +1 more
TL;DR: The original, agent based, seceder model is turned into a model of network evolution and it is found that the structural characteristics of the model closely match empirical social networks.
Journal ArticleDOI
The exponential degree distribution in complex networks: Non-equilibrium network theory, numerical simulation and empirical data
TL;DR: Inspired from the non-equilibrium network theory, a network is constructed according to two mechanisms: growing and adjacent random attachment and using the Kolmogorov–Smirnov Test (KST), it is found the simulation results are remarkably consistent with the predictions of the Non-Equilibrium Network Theory.
Journal ArticleDOI
Role of clustering and gridlike ordering in epidemic spreading
TL;DR: The two-time-step description of epidemic processes is elaborated for SIS-type epidemic processes, leading to a quantitative interpretation of the role of loops up to length 4 in the onset of an epidemic.
Journal ArticleDOI
Message-passing approach for threshold models of behavior in networks
Munik Shrestha,Cristopher Moore +1 more
TL;DR: A tractable and computationally efficient method that provides complete time evolution of each individual's probability of adopting the trend or of the frequency of adopters and nonadopters in any arbitrary networks is developed.
Proceedings ArticleDOI
Measurements, Analyses, and Insights on the Entire Ethereum Blockchain Network
TL;DR: An in-depth study of the interaction networks of the Ethereum blockchain based on several graph properties consisting of both local and global properties, which discusses their similarities and differences with social networks and the Web, draw interesting conclusions, and highlight important, future research directions.
References
More filters
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
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.