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Recognition of Opinion Leaders in Micro-Blog based on Linked Data

Volume 13, Number 6, October 2017 - Paper 9  - pp. 878-885
DOI: 10.23940/ijpe.17.06.p9.878885

Zhiyun Zheng, Pengfei Li, Xingjin Zhang, Dun Li*

School of Information Engineering,Zhengzhou University, Zhengzhou 450001, China

(Submitted on July 25, 2017; Revised on August 30, 2017; Accepted on September 15, 2017)

(This paper was presented at the Third International Symposium on System and Software Reliability.)

Abstract:

In view of the lack of subjectivity and accuracy in the traditional micro-blog opinion leader recognition method to measure the important factors of users, a new micro-blog opinion leader recognition method is proposed. This paper used the linked data to describe the micro-blog data, used the association rule mining algorithm to quantitatively determine the important factors that affected the users’ ranking, and constructed the opinion leader recognition model according to the index scoring method. Experiments show that our method using linked data identifies the opinion leaders the same as the standard leaders, is more accurate and has better feasibility than that of traditional data.

 

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