Word Sentiment Analysis using Natural Language Processing Based Techniques

Amisha Charde

Title:
Word Sentiment Analysis using Natural Language Processing Based Techniques

Authors:
Amisha Charde

Cite This Article :

Amisha Charde "Word Sentiment Analysis using Natural Language Processing Based Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Advancements and Emerging Trends in Computer Applications - Innovations, Challenges, and Future Prospects, March 2025, pp.415-419, URL: https://www.ijtsrd.com/papers/ijtsrd78540.pdf

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Abstract :
This project will deploy sentiment analysis, a major sector of Natural Language Processing (NLP), to develop a system that will find the emotions in text-based data. This system will categorize the text as Positive, Negative, or Neutral using machine-learning/deep-learning models. The primary objective is to extract actionable insights from different sources, such as social media, customer feedback, and online reviews.This system will carry out NLP processing such as tokenization, lemmatization, and vectorization, and implement various feature extraction methodologies like TF-IDF and word embeddings. Enhanced specifics rely on adding sophisticated architectures such as LSTMs and transformers for boosting accuracy. Built-in web interface via Streamlit real-time sentiment classifications done with interactive visuals. The future improvement will cover multilingual analysis, interfacing various datasets, and refining the deep learning models to tailor robustness and adaptability in sentiment predictions across different fields.

Keywords :
Sentiment Analysis, Machine Learning, Deep Learning, LSTMs, Text Preprocessing, Tokenization, Lemmatization, TF-IDF, Support Vector Machines, Naïve Bays

Publication Details:

Unique Identification Number : IJTSRD78540

Published In : Special Issue | Advancements and Emerging Trends in Computer Applications - Innovations, Challenges, and Future Prospects, March 2025

Page Number(s) : 415-419

Publisher Name : 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)

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