Publication Date: 2024/02/27
Abstract: In order to grow, businesses nowadays must ob- tain customer feedback, such as reviews or comments. They are thereby collecting additional information. The process of manually collecting and analyzing data is becoming more and more onerous for the owners of these changes. The purpose of this research is to develop an algorithm-based system that can au- tomatically extract data and support business activities. The tech- nology will reduce the effort of human workers in data analysis because it will automatically examine the entered data. It features a sentiment analysis graph. It also offers a word cloud that makes things easy to comprehend for the business administrator by displaying the most relevant keyword in different sizes according to how frequently the system identified the word from reviews or collected data. The system will forecast which department or sector of the enterprise needs improvement. The researchers will build the system using the Iterative System Design Life Cycle since it is most equipped for handling erratic behavioral shifts and even data science. Using brainstorming approaches, the project concept and approach for this study were explored or written. The instruments for requirements formulation, such as customer interviews and system functionality, usability, and security assessments, must be chosen by the researchers.
Keywords: Sentiment Analysis, Machine Learning, Feed- backs, Sentiment, Multinomial Na ̈ıve Bayes.
DOI: https://doi.org/10.5281/zenodo.10715027
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT24JAN1363.pdf
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