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

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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Bibliographic Details
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
Description
Summary: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.
ISSN:2504-4990

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