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首页> 外文期刊>International Journal of Modern Physics, B. Condensed Matter Physics, Statistical Physics, Applied Physics >Community detection in facebook activity networks and presenting a new multilayer label propagation algorithm for community detection
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Community detection in facebook activity networks and presenting a new multilayer label propagation algorithm for community detection

机译：Facebook活动网络中的社区检测并呈现用于社区检测的新多层标签传播算法

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摘要

The emergence of online social networks has revolutionized millions of web users' behavior so that their interactions with each other produce huge amounts of data on different activities. Community detection, herein, is one of the most important tasks. The very recent trend is to detect meaningful communities based on users' interactions or the activity network. However, in many of such studies, authors consider the basic network model while almost ignoring the model of the interactions in the multi-layer network. In this research, an experimental study is done to compare community detection in Facebook friendship network to that of activity network, considering different activities in Facebook OSN such as sharing. Then, a new community detection evaluation metric based on homophily is proposed. Eventually, a new method of community detection based on different activities in Facebook social network is presented. In this method, we generalized three familiar similarity methods, Jaccard, Common Neighbors and Adamic-Adar for multi-layered network model.
机译：在线社交网络的出现彻底改变了数百万的网络用户行为，以便他们与彼此的互动产生了大量的不同活动。这里，社区检测是最重要的任务之一。最近的趋势是根据用户的交互或活动网络来检测有意义的社区。然而，在许多这样的研究中，作者认为基本网络模型，同时几乎忽略了多层网络中的交互模型。在这项研究中，考虑在诸如共享等共享的Facebook OSN中的不同活动，进行实验研究以比较Facebook友谊网络中的社区检测。然后，提出了一种基于同性恋的新的社区检测评估度量。最终，提出了一种基于Facebook社交网络中不同活动的社区检测方法。在这种方法中，我们推广了三种熟悉的相似性方法，JAccard，常见邻居和多层网络模型的adamic-ADAR。

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