协作社交网络中的突变
Abrupt transitions in collaborative social networks
摘要：
尽管网络被广泛用作探索复杂社会系统的多功能工具，但人们对如何检测和预测社会系统中的突变知之甚少。在这份报告中，我们开发了一种基于网络属性的早期预警方法来检测这种变化。通过分析三个合作社交网络-一个合作明星，一个专利和一个科学合作网络，我们发现，这些网络中固有的突变可以作为一个很好的预警信号，分别指示，苏联解体，“软物质“研究领域的出现，和两个科学共同体的合并。然后，我们开发了一个集团增长模型，解释了这些真实网络的普遍性质，并发现它们属于一个新的普遍性类，由Gumbel分布描述。
英文摘要：
Despite the wide use of networks as a versatile tool for exploring complex social systems, little is known about how to detect and forecast abrupt changes in social systems. In this report, we develop an early warning approach based on network properties to detect such changes. By analysing three collaborative social networks---one co-stardom, one patent and one scientific collaborative network, we discover that abrupt transitions inherent in these networks can serve as a good early warning signal, indicating, respectively, the dissolution of the Soviet Union, the emergence of the "soft matter" research field, and the merging of two scientific communities. We then develop a clique growth model that explains the universal properties of these real networks and find that they belong to a new universality class, described by the Gumbel distribution.
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。
