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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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Machine Learning and Knowledge Extraction |
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| Online Access: | https://www.mdpi.com/2504-4990/2/4/32 |
| 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. |
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| ISSN: | 2504-4990 |