About: Characterization of Potential Drug Treatments for COVID-19 using Social Media Data and Machine Learning

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About: Characterization of Potential Drug Treatments for COVID-19 using Social Media Data and Machine Learning 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	Characterization of Potential Drug Treatments for COVID-19 using Social Media Data and Machine Learning
Creator	Banda, Juan Tekumalla, Ramya
source	ArXiv
abstract	Since the classification of COVID-19 as a global pandemic, there have been many attempts to treat and contain the virus. Although there is no specific antiviral treatment recommended for COVID-19, there are several drugs that can potentially help with symptoms. In this work, we mined a large twitter dataset of 424 million tweets of COVID-19 chatter to identify discourse around potential treatments. While seemingly a straightforward task, due to the informal nature of language use in Twitter, we demonstrate the need of machine learning methods to aid in this task. By applying these methods we are able to recover almost 15% additional data than with traditional methods, showing the need of more sophisticated approaches than just text matching.
has issue date	2020-07-20(xsd:dateTime)
has license	arxiv
sha1sum (hex)	32635edd5b6ad4bd3abdb2866a75c10b3bc997f4
resource representing a document's title	Characterization of Potential Drug Treatments for COVID-19 using Social Media Data and Machine Learning
resource representing a document's body	covid:32635edd5b6ad4bd3abdb2866a75c10b3bc997f4#body_text
is schema:about of	named entity 'recover' named entity 'Since' named entity 'MILLION' named entity 'LARGE' named entity 'APPROACHES' »more»

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