User-Generated Content Analysis: Classification of Factors Affecting Customer Needs for E-commerceRecommender System

Online selling and buying have significantly increased since COVID-19. As consumer and potential customer demand for online services increases significantly, more and more businesses are turning to electronic commerce to acquire a competitive edge. Com-panies must acknowledge and give priority to client needs if they want to compete in the market. While interviews, questionnaires, and observation are no longer effective methods for determining customer needs, as theavailability of user-generated online content (UGC) is increasing due to social networking sites (SNSs), it can be used to determine client needs to develop products or services that meet those needs. UGC has accumu-lated a wealth of information on people’s beliefs, routines, and experiences. Research on the utiliza-tion of UGC for e-commerce business applications involves various challenges and approach-es, and few studies have summarized the research work performed till now to get a clear picture. First, the study derives a general framework for summarizing the state-of-the-art research. Second, we categorize research based on the manner UGC can be classified, filtered, and understood. Further-more, we discuss models and techniques used to identify factors affecting customer needs from this content. Lastly, we identify the challenges and limitations faced in the utilization of the user-generatedcontent. To determine client wants, this study examines and categorizes user-generated content (UGC) from social net-working sites and e-commerce websites. The classification of user-gen-erated content based on context-dependent behavior, biased reviews, and minority groups has a signifi-cant impact on identifying customer demands. The limitations and difficulties of the current methods, models, and data sources are underlined. From this novel review, the researchers may get a sense of the state of the literature today and can observe the difficulties associated with categorizing reviews to identify needs. No such study has categorized the litera-ture on UGC analysis in this manner.