A classification algorithm of signed networks based on link analysis

Abstract

In the signed networks the links between nodes can be either positive (means relations are friendship) or negative (means relations are rivalry or confrontation), which are very useful for analysis the real social network. After study data sets from Wikipedia and Slashdot networks, We find that the signs of links in the fundamental social networks can be used to classified the nodes and used to forecast the potential emerged sign of links in the future with high accuracy, using models that established across these diverse data sets. Based on the models, the proposed algorithm in the artwork provides perception into some of the underlying principles that extract from signed links in the networks. At the same time, the algorithm shed light on the social computing applications by which the attitude of a person toward another can be predicted from evidence provided by their around friends relationships.