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      Friendship Maintenance and Prediction in Multiple Social Networks

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          Abstract

          Due to the proliferation of online social networks (OSNs), users find themselves participating in multiple OSNs. These users leave their activity traces as they maintain friendships and interact with other users in these OSNs. In this work, we analyze how users maintain friendship in multiple OSNs by studying users who have accounts in both Twitter and Instagram. Specifically, we study the similarity of a user's friendship and the evenness of friendship distribution in multiple OSNs. Our study shows that most users in Twitter and Instagram prefer to maintain different friendships in the two OSNs, keeping only a small clique of common friends in across the OSNs. Based upon our empirical study, we conduct link prediction experiments to predict missing friendship links in multiple OSNs using the neighborhood features, neighborhood friendship maintenance features and cross-link features. Our link prediction experiments shows that un- supervised methods can yield good accuracy in predicting links in one OSN using another OSN data and the link prediction accuracy can be further improved using supervised method with friendship maintenance and others measures as features.

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          Most cited references 5

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          Clustering and preferential attachment in growing networks

           M. Newman (2001)
          We study empirically the time evolution of scientific collaboration networks in physics and biology. In these networks, two scientists are considered connected if they have coauthored one or more papers together. We show that the probability of scientists collaborating increases with the number of other collaborators they have in common, and that the probability of a particular scientist acquiring new collaborators increases with the number of his or her past collaborators. These results provide experimental evidence in favor of previously conjectured mechanisms for clustering and power-law degree distributions in networks.
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            Scalable Link Prediction on Multidimensional Networks

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              Online Social Network Profile Linkage

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                Author and article information

                Journal
                2017-03-02
                1703.00857

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                Custom metadata
                27th ACM Conference on Hypertext and Social Media (HT'16)
                cs.SI physics.soc-ph

                Social & Information networks, General physics

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