- Friday, Sep 5th, 2025
| TITLE | Sentiment Analysis and Prediction of Consumer Reviews of Clothing Product |
|---|---|
| ABSTRACT | Sentiment analysis is a key component of Natural Language Processing (NLP), which is essential for comprehending client sentiment and enhancing commercial tactics. This study aims to forecast the tone of consumer reviews of clothing items in order to provide businesses with relevant information. To achieve the best results, this research uses a range of machine learning models, such as Random Forest, Logistic Regression, Naïve Bayes, LSTM, KNN, Decision Tree, XG Boost, ADA Boost, and Ensemble Voting Classifier. Significant patterns and trends were found after extensive data preprocessing, which included feature engineering, data cleaning, and exploratory data analysis (EDA). Among some of the visual aids, word clouds, sentence sentiment distribution graphs, and correlation analysis where obtained and found very helpful and improved knowledge of customer attitude. To ensure that the models are accurate, precision, recall, and F1-score, performance criteria were used to test the models. These findings can help companies to advance their products or service, enhanced customer satisfaction, etc. and also get to know more of their customers preferences. Consequently, they will be in a position to enhance their selling tactics and achieve better choices. |
| AUTHOR | Anamika Singh, Anusha B Y, Anita Seetaram Bhat Dept. of Computer Applications, CMR Institute of Technology, Bengaluru, India |
| PUBLICATION DATE | 2025-09-02 |
| VOLUME | 12 |
| DOI | DOI:10.15680/IJARETY.2025.1204062 |
| 62_Sentiment Analysis and Prediction of Consumer Reviews of Clothing Product.pdf | |
| KEYWORDS |
Copyright © IJARETY 2023 All Rights Reserved.