Designing an Effective Sentiment Analysis System Using Naive Bayes Algorithm
Aiswarya M Nair, G S Ajith · Zenodo (CERN European Organization for Nuclear Research) · 2023
Abstract—This paper is delivered to calculate the sentiment analysis and visualize the customer feedback about the catering services and other facilities provided by thecatering agency in a catering management system using the Naive Bayes algorithm. It helps the management of the catering agency upgrade their services and find out what customers expect about the food and services. It provides anonymity for the customer. That is, no one knows the identity of the customer who provided the feedback.The feedback entered by the customer is only visible to the administration team of the catering agency. The agency can add its products according to the customer's needs. The proposed system will also provide a visualization of the feedback data. Due in large part to the rise in consumer reviews, the fields of sentiment analysis and opinion mining have the potential to significantly impact contemporary enterprises. However, most existing sentiment analysis techniques determine if evaluations are positive or negative without elucidating the precise motives for a customer's remarks. This makes it challenging for other customers to comprehend the particular aspects being emphasized and for the product manufacturers to respond to any concerns brought up in reviews. Reviews frequently don't include thorough descriptions of the features of the product. To overcome these limitations, experts have proposed a method based on features and sentiment evaluation. This approach uses tools like Text Blob to predict the opposites of product features based on reviews This makes it possible to understand feedback from consumers better.