Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Indonesian Journal of Electrical Engineering and Computer Science
Kusum Kusum
Manav Rachna International Institute of Research& Studies

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Sentiment analysis using global vector and long short-term memory Kusum Kusum; Supriya P. Panda
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i1.pp414-422

Abstract

Tweet sentiment analysis is a Deep Learning study that is beneficial for automatically determining public opinion on a certain topic. Using the Long Short-Term Memory (LSTM) algorithm, this paper aims to proposes a Twitter analysis technique that divides Tweets into two categories (positive and negative). The Global Vector (GloVe) word embedding score is used to rate many selected words as network input. GloVe converts words into vectors by building a corpus matrix. The GloVe outperforms its prior model, owing to its smaller vector and corpora sizes. GloVe has a higher accuracy than the model word embedding word2vec, Continuous Bag of Word(CBoW), and word2vec Skip-gram. The preprocessed term variation was conducted to test the performance of sentiment classification. The test results show that this proposed method has succeeded in classifying with the best results with an accuracy of 95.61%.
Co-Authors Supriya P. Panda