Enhancing E-Commerce Insights: Sentiment Analysis Using Machine Learning and Ensemble Techniques
Shubham Shedekar, Sahil K. Shah, Vidya Kumbhar · 2023
This research aims to explore the impact of customer reviews on consumer decisions in the e-commerce era. Machine learning techniques, including Naive Bayes, Random Forest, Decision Tree, Extra Trees, and Logistic Regression, are utilized for sentiment analysis of customer reviews. A comprehensive dataset is collected through web scraping and subjected to exploratory data analysis (EDA) to gain a deeper understanding of its characteristics. Feature extraction techniques are applied to convert raw text data into meaningful numerical representations. The ensemble learning approach, specifically the voting ensemble method, is employed to combine individual model predictions, enhancing overall performance and robustness. The findings contribute valuable insights into customer sentiment, empowering businesses to understand preferences and enhance their offerings.