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Social circle discovery in ego-networks by mining the latent structure of user connections and profile attributes

机译:通过挖掘用户连接和配置文件属性的潜在结构,在自我网络中发现社交圈

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Online Social Networks (OSN) allow their users to organize their friends into groups, also known as social circles. These social circles can be used to better manage who has access to users' posted content and also to control the content posted from other users that they view. Unfortunately, these social circles are generated manually and this can be a laborious process for users with more than a few friends. In this paper, we propose an approach for automatically generating social circles that takes into account both the profile information of the friends to be grouped and the social network connectivity between them, while it allows multiple membership of friends in social circles. The approach is based on an adaptation of the widely used Latent Dirichlet Allocation model and, despite the fact that it does not explicitly model social network connectivity, as other state of the art methods do, it manages to achieve results that are competitive and even better than those obtained from such methods, at a considerably lower computational cost.
机译:在线社交网络(OSN)允许其用户将其朋友组织成组,也称为社交圈。这些社交圈可以用来更好地管理谁有权访问用户发布的内容,还可以控制他们查看的其他用户发布的内容。不幸的是,这些社交圈是手动生成的,对于拥有多个朋友的用户而言,这可能是一个费力的过程。在本文中,我们提出了一种自动生成社交圈的方法,该方法同时考虑了要分组的朋友的个人资料信息和他们之间的社交网络连接性,同时允许社交圈中的朋友成为多个成员。该方法基于对广泛使用的潜在Dirichlet分配模型的改编,尽管它没有像其他先进方法那样对社交网络连接进行显式建模,但它设法取得了竞争甚至更好的结果。与通过这种方法获得的结果相比,计算成本要低得多。

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