In recent years, Social Network Service (SNS) is a novel, popular way to make friends and convey information online. Therefore, the analysis of network data has attracted a lot of attention. It is an area that is rapidly growing, both with Statistics and Computer Science. This paper rst provides a summary of statistical methods used in network data analysis, including basic denitions, measurements, and descriptive statistics. We then introduce the Exponential Random Graph Model to t network data. Secondly, we dig into a more specic area of network analysis: Community Detection. We discuss two dierent methods to explore the community stucture, one is Louvain algorithm and the other is Mixed Membership Stochastic Blockmodels. After that, we combine the community identication with a two-stage user similarity algorithm to build a friend recommendation method. In the empirical study section, we apply this method to a real-world dataset and evaluate its performace through specic measurements.