Based on advances in computing technology and information technology, social networks have emerged as a new tool for people to exchange information and build interaction networks, and have become a key topic for social software studies in social computing. Social network forensics seeks to acquire, organize, analyze and visualize user information as direct, objective and fair evidence from a third-party perspective. Along with the rapid development of the Internet, social network forensics faces new challenges in dealing with user information being diverse, real-time and dynamic, huge in volume, and interactive, and also photo trustworthiness. It therefore has become a hot issue for opinion analysis, affective computing, content analysis in social networking relations, as well as individual, group and social behaviors in social networks and social computing. This paper designs a forensic model for social network forensics, and implements it on Sina microblogging. This model provides user information analysis, facial image recognition, and location presentation for trustworthiness analysis of digital evidence, and applies visualization to help reduce the difficulty of analysis and forensics on massive data from social networks.