Sentiment Analysis System for Hindi–English Text using Machine Learning

Ms . K Gangothri 1
Assistant Professor, Department ofAI&DSAnnamacharya Institute of Technology
and Sciences, Tirupati – 517520, A.P.gangakonkala@gmail.com
M Navya4
Department of AI&DSAnnamacharya Institute of Technologyand Sciences, Tirupati – 517520, A.P.
navya20042@gmail.com
C Rajasekhar2
Department of AI&DSAnnamacharya Institute of
Technology and Sciences, Tirupati –
517520, A.P.ganar3215@gmail.com
G Yashwanth 5
Department of AI&DSAnnamacharya Institute of
Technology and Sciences, Tirupati – 517520, A.P.
yashwanthganta507@gmail.com

A Ganesh 3
Department of AI&DSAnnamacharya Institute of
Technology and Sciences, Tirupati –517520, A.P.
ganeshavula63@gmail.com

ABSTRACT — With the rise of user-generated information in social media and other online platforms, there is an urgent requirement for the development ofautomatic systems that can analyze the opinions of people. Sentiment Analysis is one of the major applications of Natural Language Processing (NLP), which classifies the sentiments of given data into positive, negative, and neutral sentiments. This paper proposes a web-based sentiment analysis system for Hindi and English mixed text data using machine learning algorithms. The proposed system utilizes preprocessing steps such as tokenization, removal of stop words, and normalization of text data, and feature extraction using vectorization techniques. Thesystem utilizes machine learning algorithms such as Naïve Bayes and Logistic Regression for classification purposes. The system is implemented using the Django platform, which provides an easy interface for real-time sentiment prediction. The results show that the proposed system using Logistic Regression achieves an accuracy of 79%, which is suitable for real-time applications. The proposed system is highly suitable and fills the gap between theoretical and practical applications. System, Admin Module Development, Text Input System Design, File Upload Processing System, Real-Time Sentiment Prediction System, SQLite Database Management System, Backend Processing System,Frontend Interface Design, Python Programming  Language, Data Processing System, Classification ModelDevelopment, Sentiment Prediction System Development, Web-Based