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Modeling interest-based social networks: Superimposing Erdos-Renyi graphs over random intersection graphs

机译:基于兴趣的社交网络:在随机交叉图中叠加ERDOS-Renyi图形

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There is a recent rise of interest-based social networks (e.g., Pinterest and Goodreads), which connect users by relations based on shared interests. In these networks, links between users manifest from selecting common interests from a pool of available interests. For example, two users may establish a link on Pinterest because of both liking dog photos, or on Goodreads due to reading the same novel. In this paper, we introduce a random graph model to represent an interest-based social network, in consideration of users' shared interests as well as their friend relations. More specifically, the graph model is the result of superimposing an Erdos-Renyi graph (representing friendships) over a uniform random d-intersection graph (representing common interests). We present critical conditions of the model parameters so that the network is connected. Our connectivity results are useful to understand interest-based social networks and particularly beneficial for publish-subscribe services in these networks. The formally-proved results are also confirmed via experiments.
机译:最近有一个基于兴趣的社交网络(例如,Pinterest和Goodreads)的兴起,通过基于共享利益的关系来连接用户。在这些网络中,用户之间的链接清单从从可用利益池中选择共同的兴趣。例如,由于读取相同的新颖,两个用户可能在Pinterest上建立一个链接,或者由于读取同样的小说而在Goodread上。在本文中,我们介绍了一个随机图模型,以考虑到用户共享利益以及他们的朋友关系,代表基于兴趣的社交网络。更具体地,图形模型是在均匀随机D-交叉图(代表共同兴趣)上叠加ERDOS-Renyi图(代表友谊)的结果。我们呈现了模型参数的关键条件,以便连接网络。我们的连接结果可用于了解基于兴趣的社交网络,特别有利于这些网络中的发布服务。通过实验还确认了正式证明的结果。

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