CHARACTERIZING AND PREDICTING EARLY REVIEWERS FOR EFFECTIVE PRODUCT MARKETING FROM E-COMMERCE WEBSITES

Abstract

Before making a purchase, consumers might acquire useful information from online reviews. Early design reviews have a massive effect on a product's saleability. In this study, we investigate the features of early reviewers depending on their reviews on Amazon and eBay, two of the most prominent e-commerce sites.We split product lifetime into 3 categories: early, majority, and laggards. A user who has posted a review early in the process is called as an early reviewer. We quantitatively define early reviewers based on their rating behaviours, the helpfulness scores received from others, and the link among their evaluations and product popularity. We discovered that (1) early reviewers make greater insightful comments and (2) early reviewers give a greater overall rating score. According to our analysis of product reviews, early reviewers' rating and acquired usefulness score are likely to affect product popularity. Our proposed technique outperforms a range of alternative baselines in numerous tests on 2 autonomous e-commerce datasets.