关键词: 符号网络, 连边符号预测, 社交网络分析, 结构平衡理论

Abstract:

In order to make the link sign prediction more accurate in signed networks, it is necessary to analyse each underlying principle of generating signed networks. Structure balance theory and status theory are extended to gain more information for link sign prediction. A new measurement named PageTrust in web network is introduced to describe the importance of node of signed networks. On the basis of integrating different kind principles of generating signed networks, a group of refined features are extracted. Based on those creative features, two link sign predictors using supervised machine learning algorithms are established. Experimental results on two real signed networks demonstrate that learned model is more accurate and generalized than other state-of-the-art methods.

Key words: signed networks, link sign prediction, social network analysis, structure balance theory