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.