Understanding user behavior is essential for source optimization in mobile networks, including urban planning, road traffic engineering, and content distribution. In this paper, we take the first step to investigate the basic characterization of user behavior over 340,000 users of a 4G mobile network in a large metropolitan area. Our study is carried on from two aspects: mobility and application usage. In particular, the relationship between the mobility pattern and the application usage is revealed. We observe that people's mobility patterns are correlated with the application they access. Furthermore, locations such as home and workplace, affects the applications accessed by users. Utilizing our Hadoop-based mobile big data processing platform together with a systematic analysis framework of user behavior from the 6 Terabyte (TB) 4G data traffic, our analysis provides a comprehensive understanding of user behavior in 4G networks, which may be used by network operators to design appropriate mechanisms in resource provision and mobility management for resource consumers based on different categories of applications.