Identification and Ranking of Social Mining Applications in E-Commerce

In recent years, we have observed the rapid development of social media, which has drastically transformed the way in which people communicate and obtain information. Nowadays, customers on e-commerce sites mostly rely on comments posted by customers, producers, and service providers. In this research, in the first part the application of network mining is extracted using content analysis method in different dimensions of Political, Social, Economic and Technical (PEST). Then, in the second part, the applications used in two technical and economic sections are selected and using surveying expert opinion and statistical tests the more important applications have been identified among these applications. In the next step, to prioritize the applications using Analytic Hierarchy Process (AHP), paired comparisons were performed and by distributing pairwise comparison questionnaire data was collected and then the applications were ranked in order of priority. The results showed that in the economic dimension, the discovery of fraud, the discovery of the needs and interests of customers, and in the technical dimention improving e-commerce and identifying network traffic have the highest rank