Sentimental Analysis Using Deep Learning

EasyChair Preprint 13818

Abstract

A great amount of data is being evaluated in the newly-emerging field of sentiment analysis. In this approach text emotion recognition plays a crucial role.In order to produce insightful findings on a certain data. It is a powerful methodology that can benefit various domains like health care, ecommerce enterprise solution, government organisation and so on. To implement the procedure with the maximum level of accuracy researchers in the domain of natural language processing (NLP) and machine learning (ML) have investigated a number of techniques The Recurrent Neural Network (RNN) algorithm serves as its foundation. In this study, the feelings of the Internet Movie Database (IMDB) movie reviews are analysed using the Long Short-Term Memory (LSTM) classifier. The data has already been divided into 25,000 reviews for testing the classifier and 25,000 reviews for training.This model gives a accuracy of 89.9%.

Keyphrases: LSTM, Sentimental Analysis, transformer

@booklet{EasyChair:13818,
  author    = {Mahesh Mishra and Amol Patil},
  title     = {Sentimental Analysis Using Deep Learning},
  howpublished = {EasyChair Preprint 13818},
  year      = {EasyChair, 2024}}