Sentiment Analysis of Bangladeshi E Commerce Site Reviews Using Machine Learning Approaches
Journal: International Journal of Trend in Scientific Research and Development (Vol.8, No. 3)Publication Date: 2024-06-13
Authors : Mohammad Kasedullah Nakib Aman Mehedi Hasan;
Page : 442-448
Keywords : E-commerce; Daraz; Reviews; Sentiment Analysis; Multinomial Naive Bayes; Logistic Regression; Decision Tree Classifier; Random Forest Classifier; K Neighbors Classifier; Support Vector Machine; Data Cleaning;
Abstract
In the context of Bangladesh, the E commerce sector is experiencing continuous growth, particularly during the global crisis. Amidst the plethora of available platforms, Daraz has emerged as the most successful marketplace, offering users a wide array of shopping options. However, the abundance of reviews and comments on this online platform presents a challenge for consumers trying to make optimal choices. This research focuses on systematically categorizing positive and negative reviews to enhance user decision making. To achieve this objective, a range of classifiers, including Multinomial Naive Bayes, Logistic Regression, Decision Tree Classifier, Random Forest Classifier, K Neighbors Classifier, and Support Vector Machine with different kernels, were employed. The dataset underwent thorough cleaning, followed by the application of Term Frequency Inverse Document Frequency TF IDF with Principal Component Analysis PCA to enhance feature representation. The findings of this study indicate that the Multinomial Naive Bayes classifier, especially when utilizing Bigram and Trigram features, outperformed other classifiers, demonstrating superior accuracy. The implementation of this classifier holds significant promise for assisting businesses operating on various platforms, enabling them to distinguish between positive and negative reviews effectively. Consequently, this approach empowers businesses to furnish customers with valuable insights into the quality of products, contributing to a more informed and confident consumer base. Mohammad Kasedullah | Nakib Aman | Md. Mehedi Hasan "Sentiment Analysis of Bangladeshi E-Commerce Site Reviews Using Machine Learning Approaches" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-3 , June 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64875.pdf Paper Url: https://www.ijtsrd.com/engineering/computer-engineering/64875/sentiment-analysis-of-bangladeshi-ecommerce-site-reviews-using-machine-learning-approaches/mohammad-kasedullah
Other Latest Articles
- Research on the Cultivation of Sports Science Literacy and Critical Thinking in Physical Education Teacher Training
- Effects of Polypropylene on the M30 and M40 Concrete Material
- Strengthen the Impact of Online Learning on Students Audit Skills
- A Study to Assess the Level of Knowledge Regarding Life Style Modification for Prevention of Cardio Vascular Disease Among Students of Selected Colleges Lucknow
- An Experimental Study on Steel Fibre Reinforced Concrete Deep Beams with and Without Web Openings
Last modified: 2024-08-12 15:10:37