ECHOExploratory Compendium of Humanity Online

COVID-19-TweetIDs (Ongoing Collection)

LimitedVery largetextTwitter (X)CovidHealthMisinformationMultilingualTime series

A twitter dataset of 2.7B+ tweet IDs across 9+ languages (ongoing collection since Jan 2020), collected by Chen, Lerman, and Ferrara (USC Information Sciences Institute). Each record contains tweet IDs only — full content requires hydration. Largest ongoing COVID-19 Twitter collection with multilingual coverage and continuous updates since pandemic onset. Suitable for pandemic discourse, public health surveillance, infodemic analysis, multilingual NLP.

Very large: 2.8B records. Working with all of it takes more than a laptop (tens of GB of memory or a disk-based graph database); a sample, or reading the files in a streaming way, is the usual way to start.

#Infodemic#Public health surveillance#Tweet ids

Cite this dataset at covid19-tweetids.echo.directory

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Analytics

Data availability: Tweet IDs — hydration required

  • Tweet IDs only — full content requires Twitter API hydration
  • Twitter Academic Research API (free tier) retired — hydration now requires paid access

Ongoing collection of COVID-19-related tweets since January 21, 2020. ~2.7 billion tweet IDs as of last update. ~6% of tweets are deleted upon hydration. Known data gaps exist — see GitHub README. Multilingual coverage across 9+ languages. Use twarc, Hydrator, or DocNow to rehydrate. Twitter/X API now requires paid access.

2.8B
Tweet IDs
2020-01-21
Start Date
Ongoing
Status
9+
Languages
Twitter API (paid)
Hydration

Record

Catalog key
covid19_tweetids
Authors
Chen, Emily; Lerman, Kristina; Ferrara, Emilio
Year
2020
DOI / arXiv
10.2196/19273
License
CC BY-NC-SA 4.0 (CC-BY-NC-SA-4.0)
Records
2,775,946,436
Languages
de, en, es, fr, in, it, ja, pt, th
Collected
2020-01-21 to present (2020s)
Region
Global (inferred: the platform is used worldwide)

Provenance

Originally published at
https://github.com/echen102/COVID-19-TweetIDs link checked
Hosted copy
Mirrored on echo.directory on 2026-10-16, 51.7 GB across 26920 files. Checksums in MANIFEST.json.

Citations

Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set
Emily Chen, Kristina Lerman, Emilio Ferrara
Journal Article · JMIR Public Health and Surveillance · 2020

733
citations
well cited
55
influential citations
8% of all citations

Cited by

Show all 10

Citation data from Semantic Scholar, retrieved 2026-10-19.

How to cite

BibTeX

@misc{echo2026,
  title  = {ECHO: Exploratory Compendium of Humanity Online},
  author = {Switzer, Braden and Zafarani, Reza},
  year   = {2026},
  url    = {https://echo.directory},
  note   = {Syracuse University}
}

@article{chen2020tracking,
  title   = {Tracking Social Media Discourse About the COVID-19 Pandemic},
  author  = {Chen, Emily and Lerman, Kristina and Ferrara, Emilio},
  journal = {JMIR Public Health and Surveillance},
  volume  = {6},
  number  = {2},
  pages   = {e19273},
  year    = {2020},
  doi     = {10.2196/19273}
}

APA

Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory

Chen, E., Lerman, K., & Ferrara, E. (2020). COVID-19-TweetIDs (Ongoing Collection) [Data set]. https://doi.org/10.2196/19273

MLA

Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.

Chen, Emily, et al. COVID-19-TweetIDs (Ongoing Collection). 2020, doi.org/10.2196/19273.

BibTeX · RIS · CSL-JSON

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