Voat — v/Health

A Voat (Reddit alternative, 2013–2020) dataset of 2,761 submissions, 3,838 comments, 1,529 users, 2,435 collaboration edges, collected by Mekacher & Papasavva (ICWSM 2022) via full platform crawl. Each record contains user nodes (registration date, moderation status), directed weighted edges (commenter→submitter, weight=upvotes+1), submission titles and bodies, comment text, upvotes, downvotes, depth. Complete dataset for the Voat subverse v/Health, covering its full lifetime on the platform (2013–2020). Includes all 2,761 submissions and 3,838 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

#Platform migration#Subverse

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Analytics

The interactive network needs JavaScript.

· graph.json

The full graph has 1,529 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.

1.5K
Nodes
2.4K
Edges
1.04e-03
Density
44
Components
-0.1566
Assortativity
0.1%
Reciprocity
948
Bridges
Most central nodes
killer70.1571
european0.0962
boekanier0.09359
Thisismyvoatusername0.04908
Owlchemy0.0445
Conspirologist0.03207
smokratez0.0301
carnold030.02814
ratsmack0.02814
Maxcactus0.02618
Content metrics

6,599 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

upvotesμ 2.68 ± 5.603
min 0max 136
downvotesμ 0.796 ± 2.047
min 0max 30
scoreμ 1.884 ± 5.849
min -28max 134
is link post88.5% true
true 88.5%false 11.5%
depthμ 0.672 ± 1.957
min -1max 28
8.4
Flesch–Kincaid grade
US school grade level
8.9
Automated readability index
Frequent terms
peoplehealthlikemessageautomateddonstudynewknowusercancerdeletedaccountgoodtimefoodeatdiseasebodyfatusedayneedyearsriskthinksaidfounddietworkwaylifeheartmedicalyeareatinghighskinwatchresearchhealthybloodbetterdrugrightbestbrainweightchildrenshit
Topic clusters

Topic 0

eat
fat
weight
food
diet
lose
sugar
obesity

Topic 1

know
thank
wrong
interesting
right
discuss
like
good

Topic 2

coronavirus
vaccine
flu
virus
cdc
outbreak
covid
hiv

Topic 3

vaccine
people
flu
virus
case
like
coronavirus
know

Topic 4

eat
food
diet
fat
like
body
people
high

Topic 5

delete
account
user

Topic 6

marijuana
cancer
drug
opioid
cannabis
cost
overdose
die

Topic 7

woman
treatment
abortion
best
women
transplant
pain
clinic

Topic 8

fuck
faggot
nigger
shit
spammer
spam
cunt
fucking

Topic 9

tooth
alzheimer
pollution
dementia
risk
dental
disease
dentist

Topic 10

youtube
automate
message
fda
approve
adams
james
madness

Topic 11

skin
cream
serum
age
wrinkle
lotion
pop
formula
Top hashtags
#abcdrbchat2
#carehomemurder2
#scamdemic2
#11
#1387901
#297661
#566581
#684661
#848781
#890331
#9681
#__sec1title1
#breakupwithbacon1
#haes1
#murica_fuck_yah1
#newworldnextweek1
#numberoneally1
#oregoons1
#painmonth151
#top1
Top emoji
👉1
😁1
😐1
😨1
🙏1

Computed over the full corpus.

Record

Catalog key
voat-health
Authors
Mekacher, Amin; Papasavva, Antonis
Year
2022
Source paper
"I Can’t Keep It Up." A Dataset from the Defunct Voat.co News Aggregator
DOI / arXiv
10.1609/icwsm.v16i1.19382
License
Creative Commons Attribution 4.0 International (CC BY 4.0) (CC-BY-4.0)
Records
6,548
Nodes
1,529
Edges
2,435 (directed)
Attributes
nodes have attributes; edges have attributes
Languages
en
Collected
2014/2020 (2010s, 2020s)
Tasks
From the graph: link prediction, community detection
Region
Global (inferred: the platform is used worldwide)

Provenance

Originally published at
https://zenodo.org/records/5841668 link checked
Hosted copy
Mirrored on echo.directory on 2026-10-09, 14.8 MB across 4 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}
}

@article{Mekacher_2022,
  title     = {“I Can’t Keep It Up.” A Dataset from the Defunct Voat.co News Aggregator},
  volume    = {16},
  issn      = {2162-3449},
  url       = {http://dx.doi.org/10.1609/icwsm.v16i1.19382},
  doi       = {10.1609/icwsm.v16i1.19382},
  journal   = {Proceedings of the International AAAI Conference on Web and Social Media},
  publisher = {Association for the Advancement of Artificial Intelligence (AAAI)},
  author    = {Mekacher, Amin and Papasavva, Antonis},
  year      = {2022},
  month     = May,
  pages     = {1302–1311}
}

APA

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

Mekacher, A., & Papasavva, A. (2022). Voat — v/Health [Data set]. https://doi.org/10.1609/icwsm.v16i1.19382

MLA

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

Mekacher, Amin, and Antonis Papasavva. Voat — v/Health. 2022, doi.org/10.1609/icwsm.v16i1.19382.

BibTeX · RIS · CSL-JSON

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