利用友谊悖论检测未知网络的大多数核心角色

S. M. Alam, N. Islam, M. S. Hosain
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引用次数: 2

摘要

在社交网络中,大多数核心人物在商业沟通、知识传播、病毒式营销等领域的影响力大于其他人。数字信息可用的网络,如电子邮件通信,电话等,可以很容易地找到使用社会网络分析工具的核心角色。但对于那些无法获得此类信息的网络,例如偏远村庄的农民,犯罪组织的秘密网络等,找到核心参与者是具有挑战性的。我们称这种网络为未知网络。在本研究中,我们提出了一种基于友谊悖论(FP)思想的方法,从未知网络中寻找最突出的行动者。大量的仿真结果表明,我们的方法只需探索未知社会网络的一小部分人口,就能以较高的精度找到最多的中心。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detecting most central actors of an unknown network using friendship paradox
Most central people have more influence on business communication, knowledge diffusion, viral marketing and some other fields over other persons in a social network. Networks for which digital information is available such as email communication, phone call etc., one can easily find central actors using social network analysis tools. But for networks where no such information is available, for example farmers in a remote village, secret networks of a criminal organization etc., finding central actors is challenging. We call such network as unknown network. In this research, we have propose a method based on the idea of friendship paradox (FP) to find the most prominent actors from an unknown network. Extensive simulation results demonstrate that our method finds the most centrals by exploring only a small population of an unknown social network with a high accuracy.
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