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1.
Chaos ; 24(3): 033113, 2014 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-25273193

RESUMO

Recently, the impacts of spatiotemporal heterogeneities of human activities on spreading dynamics have attracted extensive attention. In this paper, we intend to understand how the heterogeneous distribution of response times at the individual level influences information spreading. Based on the uncorrelated scale-free networks without degree-degree correlation, we study the susceptible-infected spreading dynamics with adjustable power-law response time distribution, and find that the stronger the heterogeneity of response times is, the faster the information spreading is in the early and middle stages. Following a given heterogeneity, the procedure of reducing the correlation between the response times and degrees of individuals can also accelerate the spreading dynamics in the early and middle stages. However, the dynamics in the late stage is slightly more complicated, and there is an optimal value of the full prevalence time (i.e., the time for full infection on a network) changing with the heterogeneity of response times and the response time-degree correlation, respectively. The optimal phenomena result from the efficient allocation of heterogeneous response times.

2.
PLoS One ; 7(12): e50702, 2012.
Artigo em Inglês | MEDLINE | ID: mdl-23272067

RESUMO

Although the structural properties of online social networks have attracted much attention, the properties of the close-knit friendship structures remain an important question. Here, we mainly focus on how these mesoscale structures are affected by the local and global structural properties. Analyzing the data of four large-scale online social networks reveals several common structural properties. It is found that not only the local structures given by the indegree, outdegree, and reciprocal degree distributions follow a similar scaling behavior, the mesoscale structures represented by the distributions of close-knit friendship structures also exhibit a similar scaling law. The degree correlation is very weak over a wide range of the degrees. We propose a simple directed network model that captures the observed properties. The model incorporates two mechanisms: reciprocation and preferential attachment. Through rate equation analysis of our model, the local-scale and mesoscale structural properties are derived. In the local-scale, the same scaling behavior of indegree and outdegree distributions stems from indegree and outdegree of nodes both growing as the same function of the introduction time, and the reciprocal degree distribution also shows the same power-law due to the linear relationship between the reciprocal degree and in/outdegree of nodes. In the mesoscale, the distributions of four closed triples representing close-knit friendship structures are found to exhibit identical power-laws, a behavior attributed to the negligible degree correlations. Intriguingly, all the power-law exponents of the distributions in the local-scale and mesoscale depend only on one global parameter, the mean in/outdegree, while both the mean in/outdegree and the reciprocity together determine the ratio of the reciprocal degree of a node to its in/outdegree. Structural properties of numerical simulated networks are analyzed and compared with each of the four real networks. This work helps understand the interplay between structures on different scales in online social networks.


Assuntos
Amigos , Apoio Social , Comportamento , Simulação por Computador , Humanos , Internet , Funções Verossimilhança , Modelos Estatísticos , Modelos Teóricos , Probabilidade , Reprodutibilidade dos Testes
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