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Understanding community patterns in large attributed social networks

机译:了解大型归属社交网络中的社区模式

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There is an inherent presence of communities in online social networks. These communities can be defined based on i) link structure or ii) the attributes of individuals. Attributes can indicate as interests in specific topics, like science-fiction books or romantic movies, or more in general their explicit affiliation to a group inside the network. In this paper, we analyze community structures as defined by how people are associated to third concepts like attributes. To understand the community patterns we analyze three large and one small social network datasets. Our analysis shows that, irrespective of the number of nodes for any particular interest in the network, at least 50% of the nodes are part of the same connected component in the graph induced by each interest. Another interesting result of our analysis is that the majority of sub-communities (50% or above) for any interest are separated by small hops (two to three) from each other.
机译:在线社交网络中的社区存在内在存在。这些社区可以基于I)链接结构或II)来定义个体的属性。属性可以作为特定主题的兴趣指示,如科幻书籍或浪漫电影,或者更多地将其明确的网络联系到网络内的一个小组。在本文中,我们分析了人们如何与属性等第三概念相关的社区结构。要了解我们分析三个大型社交网络数据集的社区模式。我们的分析表明,无论网络中是否有任何特定兴趣的节点数量,至少50%的节点都是每个兴趣引起的图​​表中相同连接分量的一部分。我们分析的另一个有趣的结果是,任何兴趣的大多数子社区(50%或以上)都会被小啤酒花(两到三个)彼此分开。

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