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Sentiment Analysis of Student Feedback Using Natural Language Processng and Machine Learning

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Volume-10 | Issue-5

Last date : 27-Oct-2026

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Sentiment Analysis of Student Feedback Using Natural Language Processng and Machine Learning


Kalash Gadhave



Kalash Gadhave "Sentiment Analysis of Student Feedback Using Natural Language Processng and Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications, March 2026, pp.417-430, URL: https://www.ijtsrd.com/papers/ijtsrd101633.pdf

Student feedback plays a crucial role in evaluating teaching effectiveness, course quality, and overall academic experience. However, manually analyzing large volumes of textual feedback is time-consuming and prone to bias. With the rapid growth of educational institutions and digital feedback systems, there is a need for an automated and intelligent approach to analyze student opinions efficiently. This project presents a Student Feedback Sentiment Analysis system using Natural Language Processing (NLP) and Machine Learning (ML) techniques to automatically classify feedback into Positive, Negative, and Neutral categories. The proposed system processes raw student feedback text through several stages including text preprocessing, feature extraction using TF-IDF, and sentiment classification using college-safe machine learning algorithms such as Naive Bayes, Logistic Regression, and Support Vector Machine (SVM). The dataset consists of real student feedback collected at the college level. Experimental results show that the proposed approach achieves high accuracy and reliable sentiment classification performance. The system helps educational institutions identify strengths and weaknesses in teaching methodologies, course structure, and infrastructure, enabling data-driven decision-making for academic improvement.

Student Feedback Analysis; Sentiment Analysis; Natural Language Processing; Machine Learning; Text Classification


IJTSRD101633
Special Issue | Smart Innovations in Computer Science and Applications, March 2026
417-430
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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