A Twitter narrative of the COVID-19 pandemic in Australia
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Abstract (arXiv)
Social media platforms contain abundant data that can provide comprehensive knowledge of historical and real-time events. During crisis events, the use of social media peaks, as people discuss what they have seen, heard, or felt. Previous studies confirm the usefulness of such socially generated discussions for the public, first responders, and decision-makers to gain a better understanding of events as they unfold at the ground level. This study performs an extensive analysis of COVID-19-related Twitter discussions generated in Australia between January 2020, and October 2022. We explore the Australian Twitterverse by employing state-of-the-art approaches from both supervised and unsupervised domains to perform network analysis, topic modeling, sentiment analysis, and causality analysis. As the presented results provide a comprehensive understanding of the Australian Twitterverse during the COVID-19 pandemic, this study aims to explore the discussion dynamics to aid the development of future automated information systems for epidemic/pandemic management.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Feb 2023.
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Citing papers per year: 2023: 2; 2024: 2; 2025: 1.
5 papers.
- 2023Sentiment Analysis and Text Analysis of the Public Discourse on Twitter about COVID-19 and MPoxcited by 8
- 2023CrisisTransformers: Pre-trained language models and sentence encoders for crisis-related social media textscited by 7
- 2024CReMa: Crisis Response through Computational Identification and Matching of Cross-Lingual Requests and Offers Shared on Social Mediacited by 4
- 2024Semantically Enriched Cross-Lingual Sentence Embeddings for Crisis-related Social Media Textscited by 2
- 2025"Actionable Help" in Crises: A Novel Dataset and Resource-Efficient Models for Identifying Request and Offer Social Media Postscited by 0
- 2025"Actionable Help" in Crises: A Novel Dataset and Resource-Efficient Models for Identifying Request and Offer Social Media Posts24 Feb 2025
- 2024CReMa: Crisis Response through Computational Identification and Matching of Cross-Lingual Requests and Offers Shared on Social Media20 May 2024
- 2024Semantically Enriched Cross-Lingual Sentence Embeddings for Crisis-related Social Media Texts25 Mar 2024
- 2023Sentiment Analysis and Text Analysis of the Public Discourse on Twitter about COVID-19 and MPox17 Dec 2023
- 2023CrisisTransformers: Pre-trained language models and sentence encoders for crisis-related social media texts11 Sep 2023