Structural link analysis and prediction in microblogs
Proceedings of the 20th ACM international conference on Information and knowledge management
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Link prediction in Microblogs by using unsupervised methods aims to find an appropriate similarity measure between users in the network. However, the measures used by existing work lack a simple way to incorporate the structure of the network and the interactions between users. In this work, we define the retweet similarity to measure the interactions between users in Twitter, and propose a structural-interaction based matrix factorization model for following-link prediction. Experiments on the real world Twitter data show our model outperforms state-of-the-art methods.