When microblog users search someone, they would like to follow by keywords. Most service providers order their results list simply depending on the scale of followers. Unfortunately, this approach gives frauds quite a few opportunities to cheat the search engine. This paper, by regarding microblog users as Web pages, and the relationship between followers as the one between Web pages that linked each other, applied the basic idea of PageRank to rank microblog users. After introducing a statetransition matrix and an autoiterative MapReduce workflow to parallel the computation steps, this paper described a user ranking algorithm for microblog search. As shown in the experiment by using Hadoop platform, the algorithm increases the difficulty to cheat search engines, makes more important users get better rankings, and improves the relevance and quality of search results.