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Student Sentiment Analysis System Using Machine Learning Techniques

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Student Sentiment Analysis System Using Machine Learning Techniques


Khushi Wanve



Khushi Wanve "Student Sentiment Analysis System Using Machine Learning Techniques" 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.1386-1402, URL: https://www.ijtsrd.com/papers/ijtsrd102040.pdf

When assessing the efficacy of instruction, the caliber of the curriculum, and the overall academic experience, student feedback is essential. However, it is ineffective and frequently inconsistent to manually analyze vast amounts of unstructured textual feedback. In order to automatically classify student feedback into three categories—positive, neutral, and negative—this study suggests a Student Sentiment Analysis System that makes use of transformer-based deep learning techniques. The system uses self-attention mechanisms and a transformer architecture based on RoBERTa to capture contextual relationships within text. The suggested model creates contextual embeddings that interpret sentiment based on complete sentence meaning rather than isolated keywords, in contrast to conventional machine learning techniques that rely on manual feature engineering. Batch processing and real-time feedback analysis are made possible by an interactive web interface created with Streamlit. An interactive web interface developed using Streamlit enables real-time feedback analysis and batch processing. Experimental evaluation demonstrates reliable classification performance and practical applicability in educational environments. The system transforms raw textual feedback into structured sentiment insights, supporting data-driven academic decision-making.

Sentiment Analysis, Transformer Model, RoBERTa, Student Feedback, Natural Language Processing, Deep Learning.


IJTSRD102040
Special Issue | Smart Innovations in Computer Science and Applications, March 2026
1386-1402
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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