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Modeling interest-based social networks: Superimposing Erdős-Rényi graphs over random intersection graphs

机译:基于兴趣的社交网络建模:将Erdős-Rényi图叠加在随机相交图上

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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 Erdös-Rényi 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:最近出现了基于兴趣的社交网络(例如Pinterest和Goodreads),它们通过基于共享兴趣的关系将用户联系起来。在这些网络中,用户之间的链接体现为从可用兴趣池中选择共同兴趣。例如,两个用户可能会因为喜欢狗的照片而在Pinterest上建立链接,或者由于阅读同一本小说而在Goodreads上建立链接。在本文中,我们引入了一个随机图模型来表示基于兴趣的社交网络,同时考虑了用户的共享兴趣以及他们的朋友关系。更具体地说,图模型是将Erdös-Rényi图(代表友谊)叠加在均匀随机d交点图(代表共同利益)上的结果。我们介绍了模型参数的关键条件,以便连接网络。我们的连通性结果对于理解基于兴趣的社交网络非常有用,并且对于这些网络中的发布-订阅服务特别有用。正式验证的结果也通过实验得到证实。

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