Future of Information and Communication Conference (FICC) 2024
4-5 April 2024
Publication Links
IJACSA
Special Issues
Future of Information and Communication Conference (FICC)
Computing Conference
Intelligent Systems Conference (IntelliSys)
Future Technologies Conference (FTC)
International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 11, 2023.
Abstract: Since most businesses today are conducted online, it is crucial that each customer provide feedback on the various items offered. Evaluating online product sentiment and making suggestions using state-of-the-art machine learning and deep learning algorithms requires a comprehensive pipeline. Thus, this paper addresses the need for a comprehensive pipeline to analyze online product sentiment and recommend products using advanced machine learning and deep learning algorithms. The methodology of the research is divided into two parts: the Sentiment Analysis Approach and the Product Recommendation Approach. The study applies several state-of-the-art algorithms, including Naïve Bayes, Logistic Regression, Support Vector Machine (SVM), Decision Tree, Random Forest, Bidirectional Long-Short-Term-Memory (BI-LSTM), Convolutional Neural Network (CNN), Long-Short-Term-Memory (LSTM), and Stacked LSTM, with proper hyperparameter optimization techniques. The study also uses the collaborative filtering approach with the k-Nearest Neighbours (KNN) model to recommend products. Among these models, Random Forest achieved the highest accuracy of 95%, while the LSTM model scored 79%. The proposed model is evaluated using Receiver Operating Characteristic (ROC) - Area under the ROC Curve (AUC). Additionally, the study conducted exploratory data analysis, including Bundle or Bought-Together analysis, point of interest-based analysis, and sentiment analysis on reviews (1996-2018). Overall, the study achieves its objectives and proposes an adaptable solution for real-life scenarios.
Mohammed Alonazi, “Analyzing Sentiment in Terms of Online Feedback on Top of Users' Experiences” International Journal of Advanced Computer Science and Applications(IJACSA), 14(11), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0141114
@article{Alonazi2023,
title = {Analyzing Sentiment in Terms of Online Feedback on Top of Users' Experiences},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0141114},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0141114},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {11},
author = {Mohammed Alonazi}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.