Voat — v/emergencynation

A Voat (Reddit alternative, 2013–2020) dataset of 2,624 submissions, 10,776 comments, 1,600 users, 2,115 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/emergencynation, covering its full lifetime on the platform (2013–2020). Includes all 2,624 submissions and 10,776 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

#Subverse

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Analytics

The interactive network needs JavaScript.

· graph.json

The full graph has 1,600 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.

1.6K
Nodes
2.1K
Edges
8.27e-04
Density
1
Components
-0.4024
Assortativity
4.5%
Reciprocity
1.3K
Bridges
Most central nodes
7e62ce850.9475
ForTheUltimate0.1282
Othmar_Regin0.03752
0cra_tr0per0.02877
goatsshadow0.01313
CapitalPurifier0.01251
Chempergrill0.00938
Kippering0.00876
BlackSheepBrouhaha0.0075
FreshConduit0.0075
Content metrics

13,400 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

upvotesμ 5.411 ± 15.533
min 0max 237
downvotesμ 0.349 ± 0.963
min 0max 22
scoreμ 5.062 ± 15.243
min -20max 236
is link post84.0% true
true 84.0%false 16.0%
depthμ 1.254 ± 2.177
min -1max 26
7.6
Flesch–Kincaid grade
US school grade level
7.9
Automated readability index
Frequent terms
peoplelikewomendonthinkgoodmenwantknowtimerightwayneedmoneygovernmentshitworkmanstatethingswhitefreenationyearsgoingpaysystembetterworldwomanfuckingdoesnfuckchildrenthingmessageusesocietynewsocialismpointsureactuallyautomatedlifelettaxrealwarlook
Topic clusters

Topic 0

good
look
like
lol
thank
know
meme
time

Topic 1

government
white
emergency
pay
nation
tax
people
taxis

Topic 2

socialism
socialist
communism
capitalism
commie
communist
capitalist
national

Topic 3

woman
man
feminist
female
feminism
divorce
male
marry

Topic 4

nigger
fuck
faggot
shit
fucking
dumb
like
jesus

Topic 5

woman
man
want
child
like
family
good
female

Topic 6

automate
youtube
message
news
tfm
rome
fall
modern

Topic 7

jews
jew
vey
jewish
israel
goyim
goy
white

Topic 8

people
nation
system
good
society
think
like
thing
Top hashtags
#14
#s3
#22
#218af1bc3da42
#metoo2
#1001
#111
#135593631
#1444881
#1466831
#1475871
#182353951
#201201
#221
#223981
#229031
#234951
#259731
#260431
#358881
Top emoji
🔴21
😂5
🤔3
🇧1
🇬1
🇸1
🇺1
🏁1
👌1
💎1
🔹1
😀1
😁1
😉1
😒1

Computed over the full corpus.

Record

Catalog key
voat-emergencynation
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
12,968
Nodes
1,600
Edges
2,115 (directed)
Attributes
nodes have attributes; edges have attributes
Languages
en
Collected
2017/2020 (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, 18.3 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/emergencynation [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/emergencynation. 2022, doi.org/10.1609/icwsm.v16i1.19382.

BibTeX · RIS · CSL-JSON

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