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.