A Review on Machine Learning and Deep Learning Models for Sentiment Analysis

• Published in: INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT Vol. 9; no. 8; pp. 1 - 9
• Main Authors: Nagar, Devkinandan, Sharma, Nikita, Tiwari, Prof. C.K.
• Format: Journal Article
• Language: English
• Published: 14.08.2025
• ISSN: 2582-3930; 2582-3930
• DOI: 10.55041/IJSREM51760

Abstract Opinion Mining and sentiment analysis of big data has been seen as an active area of research lately. It has a wide range of applications in information systems, including classifying reviews, summarizing review and other real time applications. There are promising possibilities to use sentiment analysis in real time business models. This work analyses the use of sentiment analysis for analysing customer reviews. Customer reviews are a valuable source of feedback for businesses. However, manually analyzing a large volume of reviews can be time-consuming. Sentiment analysis automates this process, providing a quick and scalable way to comprehend the overall sentiment expressed by customers. Sentiment analysis helps businesses identify positive customer experiences. By recognizing positive sentiments in reviews, companies can pinpoint what aspects of their products or services are well-received by customers. This information is crucial for reinforcing and promoting positive features. This paper presents a review on machine learning based sentiment analysis techniques and their salient features. Keywords: Data Mining, Customer Review, Sentiment Analysis, Machine Learning, Bayesian Classifier, Classification Accuracy.