Imep: Influence Maximization on Social Media with the Impact of E-Commerce Products

Friends and family have a large influence on consumer purchasing decisions. Furthermore, many internet users prefer to wait for early adopter reviews before making a purchase decision in order to reduce the risk of adopting a new product. E-commerce corporations actively construct web-based social networks that enable users to share their experiences by submitting evaluations, evaluating other people’s assessments, and talking with genuine members. They act as a starting point for online customers and a means of directing them to other shopping sites. E-commerce companies have recently begun to collect data on consumer social interactions on their websites, with the potential goal of understanding and exploiting social influence in customer purchase decisions to improve customer relationship management and boost sales. This article proposed influence maximization on Social media with the impact of the E-Commerce Products (IMEP) framework. We collect dig and yelp datasets for finding the Social Influence (SI) for E-Commerce Products (EP). The IMEP framework utilized the United Community Recognition algorithm (UCR) to find influence maximization (IM) accuracy. The experimental results are discussed with greedy clustering and the performance measures are compared.