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

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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 : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
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' »more»

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