Abstract
Process mining in the context of information systems, which consists of information flows, has been one of the major research areas in the past decade. One of the most common objectives of process mining is the automated business process discovery. There are many challenges in the business process discovery, such as spaghetti models, same-name activities, and discovering loop structures. The researchers have presented a variety of methods that focus on one or more challenges. Due to the importance of commercial systems and the diversity of flows in them, in this research, the process mining problem in the context of social commerce systems is studied. Moreover, the research objective is to present a new method for commercial process discovery that has not been considered before. The proposed method is based on network analysis methods, multi-layered networks (networks with heterogeneous relations), and attributed networks. The results obtained from the proposed method are more precise and more comfortable to understand than the previous ones.