Abstract
This paper proposes a new model for detecting missing links in social networks. A utility function is introduced that considers the node attributes as well as the network structure for the individuals to decide whether to form a link. At the same time, logistic regression is also adopted to estimate the parameters of the algorithm based on the observed network. Furthermore, this paper validates this new missing link detection method in online social networks that were established from Facebook via comparison analysis. The results demonstrate that our method outperforms other algorithms in detecting the existent links in the original network. We also perform scalability analysis with respect to our method, analyze the complexity of method and attempt to reduce our method’s complexity by deleting some of the parameters. Moreover, this study also applies our method to network evolution analysis, and it enables us to uncover the factors that promote network evolution.
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