Document Type : Original Article
Department of Computer Engineering and Information Technology, Islamic Azad University Qazvin, Iran
Department of Computer Engineering and Information Technology , Urmia University of Technology Urmia, Iran
Social media has made major changes in various e-commerce areas. One of these marketing cases is in e-commerce systems. The relationship between customers and business is very much appreciated by marketers. The use of social media by customers has given marketers the opportunity to get more information from customer feedback. Recently, in social media, marketers look for customers who have the most impact on other customers. They can influence the ideas of other customers with their opinions about a new product. In addition, influential users can have the greatest impact on specific domains. This domain may be in the domain of a product or service. Therefore, in this article influential users on social media have been studied in terms of impact in different areas. The proposed approach is for influential users using the social knowledge management approach. The knowledge cycle consists of knowledge organization, storage, retrieval, and knowledge discovery and knowledge management, where all explicit and implicit knowledge has been tried to accurately disclose affected users. In this paper, firstly, the problem was adapted to the knowledge management cycle, and in the steps of this cycle, artificial intelligence techniques such as Baysian networks were used to classify and identify influential users .In order to investigate the proposed method, various scenarios based on a variety of data sets are used for evaluation and the results of these studies show the high accuracy of the proposed method in identifying influential users.