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A large-scale COVID-19 Twitter chatter dataset for open scientific research -- an international collaboration

arXiv 2004.03688 ↗First posted 7 Apr 2020cs.SI cs.IRcited by 33

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Abstract (arXiv)

As the COVID-19 pandemic continues its march around the world, an unprecedented amount of open data is being generated for genetics and epidemiological research. The unparalleled rate at which many research groups around the world are releasing data and publications on the ongoing pandemic is allowing other scientists to learn from local experiences and data generated in the front lines of the COVID-19 pandemic. However, there is a need to integrate additional data sources that map and measure the role of social dynamics of such a unique world-wide event into biomedical, biological, and epidemiological analyses. For this purpose, we present a large-scale curated dataset of over 152 million tweets, growing daily, related to COVID-19 chatter generated from January 1st to April 4th at the time of writing. This open dataset will allow researchers to conduct a number of research projects relating to the emotional and mental responses to social distancing measures, the identification of sources of misinformation, and the stratified measurement of sentiment towards the pandemic in near real time.

Key facts. Cited by 33 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Apr 2020.

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Citing papers per year: 2021: 8; 2022: 12; 2023: 10; 2024: 0; 2025: 2; 2026: 1.

33 papers.

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  1. 2022TwiBot-22: Towards Graph-Based Twitter Bot Detectioncited by 44
  2. 2022Twitter Topic Classificationcited by 22
  3. 2021Twitter-COMMs: Detecting Climate, COVID, and Military Multimodal Misinformationcited by 16
  4. 2021Findings of the NLP4IF-2021 Shared Tasks on Fighting the COVID-19 Infodemic and Censorship Detectioncited by 14
  5. 2022METS-CoV: A Dataset of Medical Entity and Targeted Sentiment on COVID-19 Related Tweetscited by 12
  6. 2021TBCOV: Two Billion Multilingual COVID-19 Tweets with Sentiment, Entity, Geo, and Gender Labelscited by 11
  7. 2023Leveraging Large Language Models and Weak Supervision for Social Media data annotation: an evaluation using COVID-19 self-reported vaccination tweetscited by 8
  8. 2022MM-Claims: A Dataset for Multimodal Claim Detection in Social Mediacited by 6
  9. 2021Understanding the Role of Affect Dimensions in Detecting Emotions from Tweets: A Multi-task Approachcited by 4
  10. 2022Disentangled Learning of Stance and Aspect Topics for Vaccine Attitude Detection in Social Mediacited by 4
  11. 2022ArCovidVac: Analyzing Arabic Tweets About COVID-19 Vaccinationcited by 3
  12. 2021AraCOVID19-MFH: Arabic COVID-19 Multi-label Fake News and Hate Speech Detection Datasetcited by 2
21 more
  1. 2023The RW3D: A multi-modal panel dataset to understand the psychological impact of the pandemiccited by 2
  2. 2023Data and models for stance and premise detection in COVID-19 tweets: insights from the Social Media Mining for Health (SMM4H) 2022 shared taskcited by 2
  3. 2021Insight from NLP Analysis: COVID-19 Vaccines Sentiments on Social Mediacited by 1
  4. 2022Two-Stage Classifier for COVID-19 Misinformation Detection Using BERT: a Study on Indonesian Tweetscited by 1
  5. 2022Deep Learning Reveals Patterns of Diverse and Changing Sentiments Towards COVID-19 Vaccines Based on 11 Million Tweetscited by 1
  6. 2022Machine Learning-based Automatic Annotation and Detection of COVID-19 Fake Newscited by 1
  7. 2022Identifying epidemic related Tweets using noisy learningcited by 1
  8. 2023Characterizing Financial Market Coverage using Artificial Intelligencecited by 1
  9. 2023Multimodal Graph Learning for Modeling Emerging Pandemics with Big Datacited by 1
  10. 2021Variance of Twitter Embeddings and Temporal Trends of COVID-19 casescited by 0
  11. 2021Unsupervised Text Mining of COVID-19 Recordscited by 0
  12. 2022Tweet Emotion Dynamics: Emotion Word Usage in Tweets from US and Canadacited by 0
  13. 2022LEXpander: applying colexification networks to automated lexicon expansioncited by 0
  14. 2023Human Behavior in the Time of COVID-19: Learning from Big Datacited by 0
  15. 2023Characterizing the Emotion Carriers of COVID-19 Misinformation and Their Impact on Vaccination Outcomes in India and the United Statescited by 0
  16. 2023Incorporating Dictionaries into a Neural Network Architecture to Extract COVID-19 Medical Concepts From Social Mediacited by 0
  17. 2023Cooperative Network Learning for Large-Scale and Decentralized Graphscited by 0
  18. 2023Unveiling Public Perceptions: Machine Learning-Based Sentiment Analysis of COVID-19 Vaccines in Indiacited by 0
  19. 2025Fully Bayesian Approaches to Topics over Timecited by 0
  20. 2025Nested Named-Entity Recognition on Vietnamese COVID-19: Dataset and Experimentscited by 0
  21. 2026CrisisKD: Five-Stage Knowledge Distillation for Aspect-Level Sentiment and Emotion Analysis in Crisis Discoursecited by 0