Next Article in Journal
Automatic Electronic Invoice Classification Using Machine Learning Models
Previous Article in Journal
Challenges of Machine Learning Applied to Safety-Critical Cyber-Physical Systems
Article

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

Faculty of Medicine and Health Technology, Tampere University, 33720 Tampere, Finland
Mach. Learn. Knowl. Extr. 2020, 2(4), 603-616; https://doi.org/10.3390/make2040032
Received: 31 October 2020 / Revised: 26 November 2020 / Accepted: 27 November 2020 / Published: 29 November 2020
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. View Full-Text
Keywords: text classification; sentence embeddings; Twitter; natural language processing; deep learning; health informatics; COVID-19 text classification; sentence embeddings; Twitter; natural language processing; deep learning; health informatics; COVID-19
Show Figures

Figure 1

MDPI and ACS Style

Gencoglu, O. Large-Scale, Language-Agnostic Discourse Classification of Tweets During COVID-19. Mach. Learn. Knowl. Extr. 2020, 2, 603-616. https://doi.org/10.3390/make2040032

AMA Style

Gencoglu O. Large-Scale, Language-Agnostic Discourse Classification of Tweets During COVID-19. Machine Learning and Knowledge Extraction. 2020; 2(4):603-616. https://doi.org/10.3390/make2040032

Chicago/Turabian Style

Gencoglu, Oguzhan. 2020. "Large-Scale, Language-Agnostic Discourse Classification of Tweets During COVID-19" Machine Learning and Knowledge Extraction 2, no. 4: 603-616. https://doi.org/10.3390/make2040032

Find Other Styles

Article Access Map by Country/Region

1
Back to TopTop