INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Analysis of Novel Coronavirus Neural Sentiment Classification and Topic Discovery
Authors Name:
Theertha Lakshmi AM
, Dr. Ravikumar G K , Ms.Sindhu D
Unique Id:
IJSDR2208051
Published In:
Volume 7 Issue 8, August-2022
Abstract:
Internet forums and open social media platforms, including virtual care boards, offer users (people/patients) who are worried regarding medical conditions a comfortable avenue to talk and exchange intelligence with one another. The COVID-19 sickness is an infection caused by a novel coronavirus that first emerged in late December 2019. As a result of this epidemic and the virus's quick global spread, the WHO announced a phase of disaster. In order to identify diverse COVID19-related concerns from general perspectives, we employed computerized retrieval of COVID-19-related conversations from social networking sites and natural language processing (NLP) techniques based on topic modeling in this study. Additionally, we look into how to classify COVID-19 comments' sentiment using LSTM recurrent neural networks. Our findings highlight the significance of using the general public's perceptions and appropriate computational tools to comprehend COVID-19-related concerns and direct pertinent decision-making. Additionally, tests showed that the study model outperformed numerous including well machine-learning techniques for COVID-19-Sentiment Identification, with an efficiency of 81.15 percent. to aid in decision-making and to comprehend COVID-19-related difficulties. Additionally, tests showed that the study method outperformed numerous existing well machine-learning techniques for COVID-19-Sentiment Classification, with an efficiency of 81.15 percent.
Keywords:
COVID-19, Natural Language Processing, Topic modeling, Deep Learning.
Cite Article:
"Analysis of Novel Coronavirus Neural Sentiment Classification and Topic Discovery", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 8, page no.364 - 371, August-2022, Available :http://www.ijsdr.org/papers/IJSDR2208051.pdf
Downloads:
000336258
Publication Details:
Published Paper ID: IJSDR2208051
Registration ID:201106
Published In: Volume 7 Issue 8, August-2022
DOI (Digital Object Identifier):
Page No: 364 - 371
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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