Advanced Sentiment Analysis and Topic Modeling on E-Commerce Reviews: A Comparison Study Using BERT and RoBERTa on Flipkart and Amazon

Our work delves into the realm of advanced sentiment analysis and topic modeling, focusing on e-commerce reviews from Flipkart and Amazon, two major platforms. Using state-of-the-art natural language processing models, namely BERT and RoBERTa, we aim to gain a deeper understanding of customer sentiments. By utilizing pre-trained transformer models and fine-tuned sentiment analysis techniques, we were able to improve the accuracy of classifying customer sentiments. Furthermore, we conducted a comparison between BERT and RoBERTa to evaluate which model better captures the nuances of e-commerce sentiments. We took our analysis a step further by implementing Latent Dirichlet Allocation (LDA) on the embeddings generated by BERT and RoBERTa. By doing so, we aimed to uncover underlying themes within the reviews, providing valuable insights into the factors that drive customer opinions. This comparative study enables us to gain a comprehensive understanding of the effectiveness of each model in capturing the diverse aspects of e-commerce sentiments.