Year: 2025
Type: article
Abstract: Sentiment analysis, also considered as opinion mining, is a crucial element in NLP (Natural Learning Processing), which distinguishes the polarity of any text, or word, or phrase. The project aims to examine and enhance sentiment analysis abilities using machine learning models: Support vector machine (svm), Naīve Bayes, Linear regression. The raw datasets are collected and preprocessed from diverse domains to ensure a comprehensive study of this paper. Text preprocessing includes the steps: manual labelling, normalization, tokenization, stop words removal, preparing the texts for sentiment analysis. The project focuses on comparison of models to identify the suitable approach out of all. This project offers insights to different techniques, its application, limitations, strengths contributing to NLP methodologies for elevation of sentimental analysis.
Author: Afsheen Pothiyawala
Institution: Kalinga University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4409307047