Detecting the missing links in social networks based on utility analysis

作者：Luo Peng^*; Li Yongli^*; Wu Chong; Chen Kun

来源：Journal of Computational Science, 2016, 16: 51-58.

DOI：10.1016/j.jocs.2016.04.016

• Social network
• Link detection
• Logistic regression
• Network analysis
• Utility function

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.

• 出版日期2016-9
• 单位哈尔滨工业大学; 南方科技大学; 东北大学