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Evaluating community detection methods in a controlled experiment

机译:评估受控实验中的社区检测方法

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Detecting communities in non-trivial networks is a hard task that has been attracting the attention of many researchers in the field of complex networks. When the network has identical and non-overlapping communities, however, one could expect this task to be easy. We show in this paper that, surprisingly, it is not the case. For this purpose, we carried out a controlled experiment in which 9 well-known community detection methods are applied to 8 different hierarchical ring networks of 60 nodes each. None of the tested methods correctly identified the communities for all networks. Moreover, the modularity score showed a weak response in the identification of rings as communities in hierarchical ring networks. These results point to the need of discussing what community detection algorithms are actually detecting, and how to evaluate their results, both when dealing with trivial or non-trivial networks.
机译:检测非琐碎网络中的社区是一项艰难的任务,它一直引起了复杂网络领域的许多研究人员的注意力。然而,当网络具有相同和非重叠的社区时,人们可以指望这项任务很容易。我们在本文中展示,令人惊讶的是,并非如此。为此目的,我们进行了一个受控实验,其中9个众所周知的社区检测方法应用于每个60节点的8个不同的分层环网络。没有任何测试的方法正确识别所有网络的社区。此外,模块化分数在识别环形环网中的社区的识别中显示出弱响应。这些结果指出需要讨论社区检测算法实际检测的内容,以及如何在处理琐碎或非琐碎网络时评估其结果。

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