User - analysis techniques are mainly used to recommend friends and information. This paper discusses the data characteristics of microblog users and describes a multidimensional user recommendation algorithm that takes into account microblog length, relativity between microblog and users, and familiarity between users. The experimental results show that this multidimensional algorithm is more accurate than a traditional recommendation algorithm.