Information dynamics shape the networks of Internet-mediated prostitution

Like many other social phenomena, prostitution is increasingly coordinated over the Internet. The online behavior affects the offline activity; the reverse is also true. We investigated the reported sexual contacts between 6,624 anonymous escorts and 10,106 sex-buyers extracted from an online community from its beginning and six years on. These sexual encounters were also graded and categorized (in terms of the type of sexual activities performed) by the buyers. From the temporal, bipartite network of posts, we found a full feedback loop in which high grades on previous posts affect the future commercial success of the sex-worker, and vice versa. We also found a peculiar growth pattern in which the turnover of community members and sex workers causes a sublinear preferential attachment. There is, moreover, a strong geographic influence on network structure-the network is geographically clustered but still close to connected, the contacts consistent with the inverse-square law observed in trading patterns. We also found that the number of sellers scales sublinearly with city size, so this type of prostitution does not, comparatively speaking, benefit much from an increasing concentration of people

Fat-tailed fluctuations in the size of organizations: the role of social influence

Organizational growth processes have consistently been shown to exhibit a fatter-than-Gaussian growth-rate distribution in a variety of settings. Long periods of relatively small changes are interrupted by sudden changes in all size scales. This kind of extreme events can have important consequences for the development of biological and socio-economic systems. Existing models do not derive this aggregated pattern from agent actions at the micro level. We develop an agent-based simulation model on a social network. We take our departure in a model by a Schwarzkopf et al. on a scale-free network. We reproduce the fat-tailed pattern out of internal dynamics alone, and also find that it is robust with respect to network topology. Thus, the social network and the local interactions are a prerequisite for generating the pattern, but not the network topology itself. We further extend the model with a parameter $\delta$ that weights the relative fraction of an individual's neighbours belonging to a given organization, representing a contextual aspect of social influence. In the lower limit of this parameter, the fraction is irrelevant and choice of organization is random. In the upper limit of the parameter, the largest fraction quickly dominates, leading to a winner-takes-all situation. We recover the real pattern as an intermediate case between these two extremes.Comment: 15 pages, 4 figure

The contact network of patients in a regional healthcare system

Yet in spite of advances in hospital treatment, hospitals continue to be a breeding ground for several airborne diseases and for diseases that are transmitted through close contacts like SARS, methicillin-resistant Staphylococcus aureus (MRSA), norovirus infections and tuberculosis (TB). Here we extract contact networks for up to 295,108 inpatients for durations up to two years from a database used for administrating a local public healthcare system serving a population of 1.9 million individuals. Structural and dynamical properties of the network of importance for the transmission of contagious diseases are then analyzed by methods from network epidemiology. The contact networks are found to be very much determined by an extreme (age independent) variation in duration of hospital stays and the hospital structure. We find that that the structure of contacts between in-patients exhibit structural properties, such as a high level of transitivity, assortativity and variation in number of contacts, that are likely to be of importance for the transmission of less contagious diseases. If these properties are considered when designing prevention programs the risk for and the effect of epidemic outbreaks may be decreased

Finding influential spreaders from human activity beyond network location

Most centralities proposed for identifying influential spreaders on social networks to either spread a message or to stop an epidemic require the full topological information of the network on which spreading occurs. In practice, however, collecting all connections between agents in social networks can be hardly achieved. As a result, such metrics could be difficult to apply to real social networks. Consequently, a new approach for identifying influential people without the explicit network information is demanded in order to provide an efficient immunization or spreading strategy, in a practical sense. In this study, we seek a possible way for finding influential spreaders by using the social mechanisms of how social connections are formed in real networks. We find that a reliable immunization scheme can be achieved by asking people how they interact with each other. From these surveys we find that the probabilistic tendency to connect to a hub has the strongest predictive power for influential spreaders among tested social mechanisms. Our observation also suggests that people who connect different communities is more likely to be an influential spreader when a network has a strong modular structure. Our finding implies that not only the effect of network location but also the behavior of individuals is important to design optimal immunization or spreading schemes

Patrones de contacto social y dinámica de las enfermedades

Las enfermedades transmisibles han constituido históricamente una amenaza muy grave para la sociedad. La epidemia del SIDA, el brote de SARS y la posibilidad del bioterrorismo han dejado claro que esta amenaza sigue presente. La creciente amenaza que las enfermedades infecciosas suponen para la sociedad contemporánea es en gran medida el resultado de nuestro estilo de vida moderno, sobre todo a causa del gran número de interacciones sociales a nivel global posibles en un corto período de tiempo. Más que nunca, los patrones de contacto social son fundamentales para entender la dinámica de las enfermedades infecciosas. En este documento se comentan los principales aspectos de los modelos epidemiológicos y de los patrones de contacto que deben tenerse en cuenta y se destaca la interacción existente entre las características de las enfermedades y los patrones de interacción social. También se discuten las similitudes y diferencias existentes entre los patrones de interacción social de la sociedad actual y las sociedades de antaño y las consecuencias de ambas en la dinámica de las enfermedades

Problemas y estrategias para combatir las pandemias a la luz de la gripe aviar de 2005

Este análisis se centra en la importancia de poner en marcha una estrategia de lucha contra enfermedades infecciosas que tenga en cuenta los patrones de interacción humana al intentar combatir una pandemia en la sociedad moderna. Este análisis estudia la importancia de considerar los patrones de contacto social de los individuos de una región tanto al decidir qué estrategia de vacunación emplear como al intentar limitar los contactos en la región en caso de una gran pandemia. El análisis incluye una breve introducción a los brotes recientes de nuevas enfermedades infecciosas, como el SIDA y el SARS. Llegamos a la conclusión de que a la hora de diseñar una estrategia de vacunación para impedir una mayor propagación de una enfermedad resulta más efectivo tener en cuenta los patrones de interacción social (centrándose en quienes viajan largas distancias, en individuos con gran cantidad de contactos diarios y en aquéllos con mayor riesgo de entrar en contacto con individuos contagiosos, como quienes trabajan en sanidad) que adoptar un enfoque más aleatorio o centrado en los individuos más vulnerables