Large-Scale, Language-Agnostic Discourse Classification of Tweets During COVID-19

Quantifying the characteristics of public attention is an essential prerequisite for appropriate crisis management during severe events such as pandemics. For this purpose, we propose language-agnostic tweet representations to perform large-scale Twitter discourse classification with machine learnin...

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Main Author:	Oguzhan Gencoglu
Format:	Article
Language:	English
Published:	MDPI AG 2020-11-01
Series:	Machine Learning and Knowledge Extraction
Subjects:	text classification sentence embeddings Twitter natural language processing deep learning health informatics
Online Access:	https://www.mdpi.com/2504-4990/2/4/32

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spelling	doaj-73379e732d344f778b747544cb63b1ff2020-11-30T00:01:42ZengMDPI AGMachine Learning and Knowledge Extraction2504-49902020-11-0123260361610.3390/make2040032Large-Scale, Language-Agnostic Discourse Classification of Tweets During COVID-19Oguzhan Gencoglu0Faculty of Medicine and Health Technology, Tampere University, 33720 Tampere, FinlandQuantifying the characteristics of public attention is an essential prerequisite for appropriate crisis management during severe events such as pandemics. For this purpose, we propose language-agnostic tweet representations to perform large-scale Twitter discourse classification with machine learning. Our analysis on more than 26 million coronavirus disease 2019 (COVID-19) tweets shows that large-scale surveillance of public discourse is feasible with computationally lightweight classifiers by out-of-the-box utilization of these representations.https://www.mdpi.com/2504-4990/2/4/32text classificationsentence embeddingsTwitternatural language processingdeep learninghealth informatics
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Oguzhan Gencoglu
spellingShingle	Oguzhan Gencoglu Large-Scale, Language-Agnostic Discourse Classification of Tweets During COVID-19 Machine Learning and Knowledge Extraction text classification sentence embeddings Twitter natural language processing deep learning health informatics
author_facet	Oguzhan Gencoglu
author_sort	Oguzhan Gencoglu
title	Large-Scale, Language-Agnostic Discourse Classification of Tweets During COVID-19
title_short	Large-Scale, Language-Agnostic Discourse Classification of Tweets During COVID-19
title_full	Large-Scale, Language-Agnostic Discourse Classification of Tweets During COVID-19
title_fullStr	Large-Scale, Language-Agnostic Discourse Classification of Tweets During COVID-19
title_full_unstemmed	Large-Scale, Language-Agnostic Discourse Classification of Tweets During COVID-19
title_sort	large-scale, language-agnostic discourse classification of tweets during covid-19
publisher	MDPI AG
series	Machine Learning and Knowledge Extraction
issn	2504-4990
publishDate	2020-11-01
description	Quantifying the characteristics of public attention is an essential prerequisite for appropriate crisis management during severe events such as pandemics. For this purpose, we propose language-agnostic tweet representations to perform large-scale Twitter discourse classification with machine learning. Our analysis on more than 26 million coronavirus disease 2019 (COVID-19) tweets shows that large-scale surveillance of public discourse is feasible with computationally lightweight classifiers by out-of-the-box utilization of these representations.
topic	text classification sentence embeddings Twitter natural language processing deep learning health informatics
url	https://www.mdpi.com/2504-4990/2/4/32
work_keys_str_mv	AT oguzhangencoglu largescalelanguageagnosticdiscourseclassificationoftweetsduringcovid19
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Large-Scale, Language-Agnostic Discourse Classification of Tweets During COVID-19

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