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S. Kang, “Evaluation of the Social Network’s Nodes Influence Based on Users’ Behavior and Relationship— Take Microblogging for Instance,” Master Thesis, Beijing University of Posts and Telecommunications, Beijing, 2011.

has been cited by the following article:

• TITLE: Evaluation of Microblog Users’ Influence Based on PageRank and Users Behavior Analysis

  AUTHORS: Lijuan Huang, Yeming Xiong

  KEYWORDS: Social Network; Microblog Users Behavior; PageRank Algorithms; U-R Model; Influence

  JOURNAL NAME: Advances in Internet of Things, Vol.3 No.2, April 30, 2013

  ABSTRACT: This paper explores the uses’ influences on microblog. At first, according to the social network theory, we present an analysis of information transmitting network structure based on the relationship of following and followed phenomenon of microblog users. Informed by the microblog user behavior analysis, the paper also addresses a model for calculating weights of users’ influence. It proposes a U-R model, using which we can evaluate users’ influence based on PageRank algorithms and analyzes user behaviors. In the U-R model, the effect of user behaviors is explored and PageRank is applied to evaluate the importance and the influence of every user in a microblog network by repeatedly iterating their own U-R value. The users’ influences in a microblog network can be ranked by the U-R value. Finally, the validity of U-R model is proved with a real-life numerical example.