The popularity of various online social network applications, such as Facebook, Twitter, Weibo and WeChat, has become a major source of big data, the online social network data. It contains rich information and knowledge about people's daily lives and penetrates to many domains, such as politics, business, marketing, social interaction, online education, knowledge sharing, or even homeland security. Advanced data mining techniques for online social network data lead to promising solutions in conquering the challenges in this exciting field. The objectives of this workshop are to reflect the latest development of the theories, models, algorithms and applications of online social network analysis using big data mining techniques. For example, big data in online social network applications can be analyzed or mined in many aspects, such as structure patterns in social networks, user interaction models, information dissemination patterns in social networks, as well as influence diffusion. The scope of the workshop also involves advanced techniques, such as big graph data mining, big data stream mining, and advanced search. This workshop will bring together researchers and practitioners from different related areas to share new ideas on mining big data in social networks.