Weibo-COV: A Large-Scale COVID-19 Social Media Dataset from Weibo
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Abstract (arXiv)
With the rapid development of COVID-19 around the world, people are requested to maintain "social distance" and "stay at home". In this scenario, extensive social interactions transfer to cyberspace, especially on social media platforms like Twitter and Sina Weibo. People generate posts to share information, express opinions and seek help during the pandemic outbreak, and these kinds of data on social media are valuable for studies to prevent COVID-19 transmissions, such as early warning and outbreaks detection. Therefore, in this paper, we release a novel and fine-grained large-scale COVID-19 social media dataset collected from Sina Weibo, named Weibo-COV, contains more than 40 million posts ranging from December 1, 2019 to April 30, 2020. Moreover, this dataset includes comprehensive information nuggets like post-level information, interactive information, location information, and repost network. We hope this dataset can promote studies of COVID-19 from multiple perspectives and enable better and rapid researches to suppress the spread of this pandemic.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 May 2020.
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Citing papers per year: 2022: 2; 2023: 1; 2024: 1; 2025: 3; 2026: 4.
11 papers.
- 2022Detect Rumors in Microblog Posts for Low-Resource Domains via Adversarial Contrastive Learningcited by 41
- 2024SPEED++: A Multilingual Event Extraction Framework for Epidemic Prediction and Preparednesscited by 6
- 2022Recovering Patient Journeys: A Corpus of Biomedical Entities and Relations on Twitter (BEAR)cited by 4
- 2023A Unified Contrastive Transfer Framework with Propagation Structure for Boosting Low-Resource Rumor Detectioncited by 1
- 2025Nested Named-Entity Recognition on Vietnamese COVID-19: Dataset and Experimentscited by 0
- 2025Research on Short-Video Platform User Decision-Making via Multimodal Temporal Modeling and Reinforcement Learningcited by 0
- 2025The Art of Storytelling in Authoritarian Regimes: Crafting State Narratives on Chinese Social Mediacited by 0
- 2026Large language models for spreading dynamics in complex systemscited by 0
- 2026SURGE: An Event-Centric Social Media Sentiment Time Series Benchmark with Interaction Structurecited by 0
- 2026Against Political Polarization: A Unified Framework for Tracing Evolving Political Ideologies on Social Mediacited by 0
- 2026Caught in the Story: Narrative Captivity in Multi-turn LLMs Conversationcited by 0
- 2026Caught in the Story: Narrative Captivity in Multi-turn LLMs Conversation3 Sep 2026
- 2026Against Political Polarization: A Unified Framework for Tracing Evolving Political Ideologies on Social Media18 Aug 2026
- 2026SURGE: An Event-Centric Social Media Sentiment Time Series Benchmark with Interaction Structure20 May 2026
- 2026Large language models for spreading dynamics in complex systems8 Feb 2026
- 2025The Art of Storytelling in Authoritarian Regimes: Crafting State Narratives on Chinese Social Media7 Dec 2025
- 2025Research on Short-Video Platform User Decision-Making via Multimodal Temporal Modeling and Reinforcement Learning13 Sep 2025
- 2025Nested Named-Entity Recognition on Vietnamese COVID-19: Dataset and Experiments21 Apr 2025
- 2024SPEED++: A Multilingual Event Extraction Framework for Epidemic Prediction and Preparedness24 Oct 2024
- 2023A Unified Contrastive Transfer Framework with Propagation Structure for Boosting Low-Resource Rumor Detection4 Apr 2023
- 2022Recovering Patient Journeys: A Corpus of Biomedical Entities and Relations on Twitter (BEAR)21 Apr 2022
- 2022Detect Rumors in Microblog Posts for Low-Resource Domains via Adversarial Contrastive Learning18 Apr 2022