Micro-Blogger Influence Analysis Based on User Features

摘要: Micro-bloggers with higher influence are important for information propagation and products recommendation in micro-blogging networks. In this paper, we evaluate micro-blogger's features by follower factor, spreading factor interaction integrate these user social relationship network structures into a unity graph model. Then propose an analysis algorithm Influence-Rank, which aims to quantify the micro-bloggers' influence. Experimental results show that Influence-Rank can take both connectivity characteristics account, dig out influential micro-bloggers who generation dissemination. Compared other methods, Influence- Rank shows better performance objectivity effectiveness.