CoAID: COVID-19 Healthcare Misinformation

A CoAID (COVID-19 misinformation dataset) dataset of 5,975 news articles and social media posts, collected by Cui and Lee via COVID-19 pandemic (2020-2021). Each record contains news articles, fact-check URLs, binary label (0=real, 1=fake), and temporal data. The dataset is notable for its temporally-structured dataset tracking COVID-19 misinformation evolution. Intended for research into COVID-19 misinformation detection, healthcare communication, and temporal social media analysis.

#Coaid#Timestamps

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Analytics

11.4
Flesch–Kincaid grade
US school grade level
12.9
Automated readability index
Frequent terms
covidcoronavirushealthaccesspeoplediseasenewpandemicprotectdataonline2020servicecdcwebsitesecurityvirusattackswebmdcloudflarerestrictdeniedriskinformation2019patientssarsexpertshelpcovspreadtimesymptomscasesstatescarepublicbasedvaccineoutbreakavailableworldguidancestudymedicalinfectiontestinghealthcarehomeunited
Topic clusters

Topic 0

vaccine
trial
test
flu
drug
coronavirus
new
antibody

Topic 1

pandemic
mental
people
expert
patient
doctor
time
hospital

Topic 2

coronavirus
virus
hand
spread
china
new
novel
outbreak

Topic 3

access
deny
cloudflare
restrict
attack
security
website
online

Topic 4

trump
president
bill
donald
coronavirus
governor
biden
facebook

Topic 5

access
deny
cloudflare
restrict
attack
security
website
online

Topic 6

guidance
disease
health
facility
coronavirus
healthcare
care
cdc

Topic 7

mask
face
wear
cloth
masks
covering
spread
use

Topic 8

schools
communities
event
school
workplaces
guidance
worker
community

Topic 9

symptom
cause
people
risk
severe
heart
patient
disease

Topic 10

health
world
country
global
response
support
child
organization
Top hashtags
#coronavirus13
#2019ncov12
#covid197
#beactive2
#covidwarrior2
#fakenews2
#highriskcovid192
#thankshealthheros2
#0391
#covid1
#ibuprofen1
#keepusclosed1
#magaó1
#mask1
#more1
#notmypresident1
Top emoji
🚨16
🇸5
🇺5
🗣2
🏻1
😂1
😌1
🤷1
🦠1

Computed over the full corpus.

Record

Catalog key
coaid
Authors
Cui, Limeng; Lee, Dongwon
Year
2020
Source paper
CoAID: COVID-19 Healthcare Misinformation Dataset
DOI / arXiv
10.48550/arXiv.2006.00885
License
Academic use (see GitHub) (LicenseRef-Research-Only)
Records
5,975
Languages
en
Collected
2020-2021 (2020s)

Provenance

Originally published at
https://github.com/cuilimeng/CoAID link checked
Hosted copy
Mirrored on echo.directory on 2026-10-09, 14.1 MB across 43 files. Checksums in MANIFEST.json.

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}
}

@misc{https://doi.org/10.48550/arxiv.2006.00885,
  doi       = {10.48550/ARXIV.2006.00885},
  url       = {https://arxiv.org/abs/2006.00885},
  author    = {Cui, Limeng and Lee, Dongwon},
  keywords  = {Social and Information Networks (cs.SI), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
  title     = {CoAID: COVID-19 Healthcare Misinformation Dataset},
  publisher = {arXiv},
  year      = {2020},
  copyright = {arXiv.org perpetual, non-exclusive license}
}

APA

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

Cui, L., & Lee, D. (2020). CoAID: COVID-19 Healthcare Misinformation [Data set]. https://doi.org/10.48550/arXiv.2006.00885

MLA

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

Cui, Limeng, and Dongwon Lee. CoAID: COVID-19 Healthcare Misinformation. 2020, doi.org/10.48550/arXiv.2006.00885.

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