About: Deep Sentiment Classification and Topic Discovery on Novel Coronavirus or COVID-19 Online Discussions: NLP Using LSTM Recurrent Neural Network Approach

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Deep Sentiment Classification and Topic Discovery on Novel Coronavirus or COVID-19 Online Discussions: NLP Using LSTM Recurrent Neural Network Approach Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Deep Sentiment Classification and Topic Discovery on Novel Coronavirus or COVID-19 Online Discussions: NLP Using LSTM Recurrent Neural Network Approach
Creator	Jelodar, Hamed Orji, Rita Wang, Yongli
Source	BioRxiv
abstract	Internet forums and public social media, such as online healthcare forums, provide a convenient channel for users (people/patients) concerned about health issues to discuss and share information with each other. In late December 2019, an outbreak of a novel coronavirus (infection from which results in the disease named COVID-19) was reported, and, due to the rapid spread of the virus in other parts of the world, the World Health Organization declared a state of emergency. In this paper, we used automated extraction of COVID-19–related discussions from social media and a natural language process (NLP) method based on topic modeling to uncover various issues related to COVID-19 from public opinions. Moreover, we also investigate how to use LSTM recurrent neural network for sentiment classification of COVID-19 comments. Our findings shed light on the importance of using public opinions and suitable computational techniques to understand issues surrounding COVID-19 and to guide related decision-making.
has issue date	2020-04-24(xsd:dateTime)
bibo:doi	10.1101/2020.04.22.054973
has license	biorxiv
sha1sum (hex)	1bdf3c4613936ba022e38f126f620c770e18b9ca
schema:url	https://doi.org/10.1101/2020.04.22.054973
resource representing a document's title	Deep Sentiment Classification and Topic Discovery on Novel Coronavirus or COVID-19 Online Discussions: NLP Using LSTM Recurrent Neural Network Approach
schema:publication	bioRxiv
resource representing a document's body	covid:1bdf3c4613936ba022e38f126f620c770e18b9ca#body_text
is schema:about of	named entity 'decision-making' named entity 'disease' named entity 'opinions' named entity 'World Health Organization' named entity 'Topic' named entity 'LSTM' named entity 'share' named entity 'virus' named entity 'LSTM' named entity 'COVID-19' named entity 'infection' named entity 'channel' named entity 'COVID-19' named entity 'guide' named entity '2019' named entity 'COVID-19' named entity 'Internet forums' named entity 'share information' named entity 'COVID-19' named entity 'LSTM' named entity 'reddit' named entity 'state of emergency' named entity 'pre-trained' named entity 'COVID-19' named entity 'COVID-19' named entity 'sentiment analysis' named entity 'opinion mining' named entity 'semantic' named entity 'LDA' named entity 'semantic' named entity 'COVID-19' named entity 'sampling' named entity 'NLP' named entity 'training set' named entity 'reddit' named entity 'COVID-19' named entity 'health information' named entity 'COVID-19' named entity 'sampling' named entity 'COVID-19' named entity 'online community' named entity 'COVID-19' named entity 'COVID-19' named entity 'Naive Bayes' named entity 'time complexity' named entity 'online community' named entity 'COVID-19' named entity 'COVID-19' named entity 'COVID-19' named entity 'COVID-19' named entity 'semantic' named entity 'COVID-19' named entity 'reddit' named entity 'social media' named entity 'reddit' named entity 'COVID-19' named entity 'COVID-19' named entity 'COVID-19' named entity 'COVID-19' named entity 'Algorithm' named entity 'online forums' named entity 'semantic' named entity 'sampling' named entity 'NLP' named entity 'Deep Learning' named entity 'deep learning' named entity 'online forums' named entity 'social media' named entity 'COVID-19' named entity 'LSTM' named entity 'probability' named entity 'knowledge discovery' named entity 'probability' named entity 'online forums' named entity 'COVID-19' named entity 'COVID-19' named entity 'COVID-19' named entity 'inference' named entity 'Deep neural networks' named entity 'LDA' named entity 'subreddits' named entity 'COVID-19'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software