Automated Analysis for E-Commerce Platforms: Amazon Product Reviews

We live in the age of online shopping - proliferation of Ecommerce platforms such as Amazon has become critical sources of feedback for consumers, through product reviews. With tons of data, it's hard for both the customers and sellers to extract meaningful insight manually. In this paper, we present a system for scraping Amazon Product Reviews, using sophisticated Python libraries to web scrape and perform sentiment analysis. Using a range of plots (pie charts to show sentiment distributions, word clouds of frequent terms, scatter plots of sentiment with ratings, and line plots of temporal trends), the system intuitively visualizes review data. Analyses of these plots uncover key trends such as trending sentiment over product ratings, time distribution, frequency of certain terms, and verified versus unverified purchases. Besides, these data are exported in an Excel file, which provides a complete marketing solution for both consumers and businesses to base their decisions on real customer feedback.