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arXiv 1106.5249physics.soc-phcs.SIphysics.data-an
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科学合作网络中强关系的力量

The strength of strong ties in scientific collaboration networks

Raj Kumar Pan, Jari Saramäki

摘要:

网络拓扑结构及其与领带强度的关系可能会阻碍或增强社交网络中的信息传播。我们研究了科学合作网络中的关系强度和拓扑结构之间的相关性,并表明这些网络与普通的社交网络有很大的不同。对于后者,早先已经表明,强联系与密集的网络社区相关,而较弱的联系则充当这些之间的桥梁。因此,薄弱环节成为信息传播的瓶颈。我们发现,相反,在合著网络密集的局部社区主要由弱链接,而强链接是更重要的整体连通性。强链接的重要作用在信息传播的模拟中得到进一步强调,它们的拓扑位置被认为大大加快了传播动力学。因此,与普通的社交网络相比,权重-拓扑相关性增强了跨科学合作网络的信息流。

英文摘要:

Network topology and its relationship to tie strengths may hinder or enhance the spreading of information in social networks. We study the correlations between tie strengths and topology in networks of scientific collaboration, and show that these are very different from ordinary social networks. For the latter, it has earlier been shown that strong ties are associated with dense network neighborhoods, while weaker ties act as bridges between these. Because of this, weak links act as bottlenecks for the diffusion of information. We show that on the contrary, in co-authorship networks dense local neighborhoods mainly consist of weak links, whereas strong links are more important for overall connectivity. The important role of strong links is further highlighted in simulations of information spreading, where their topological position is seen to dramatically speed up spreading dynamics. Thus, in contrast to ordinary social networks, weight-topology correlations enhance the flow of information across scientific collaboration networks.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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