MADOC: Voat / KotakuInAction

A MADOC (Voat, KotakuInAction) dataset of 1,878 users and 3,854 reply edges from 7,853 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.

#Gamergate#Kotakuinaction#Madoc#Reply network#Toxigen#Vader

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Analytics

The interactive network needs JavaScript.

· graph.json

The full graph has 1,878 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.

1.9K
Nodes
3.9K
Edges
1.09e-03
Density
41
Components
0.02867
Assortativity
0.4%
Reciprocity
1.2K
Bridges
Most central nodes
e4761dde-49c2-5dcd-ad28-3b39daa80ad40.2642
2155195b-5979-5a02-940e-44a63bc4927c0.1087
3f7993a7-57b2-52bf-8ae5-cabb823fbd270.1012
e811491c-31ed-5cec-a719-6a94875237710.09643
6e7f0be2-fb7f-50b5-ba2c-43f7dae05cc20.07459
c140d641-c263-5529-8cf8-53693ac6bed40.0634
47e12d7b-1eda-5fc8-9133-f170eb94b2cb0.04742
d5a7aed9-4125-5a8d-add7-a4cfc2cae8ec0.03942
94a8f2ac-c90d-53e0-aef1-e5eb4e4f7daa0.03942
f1b6434d-897e-5100-b4cf-afa48b1383930.03889
Content metrics

7,853 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

Sentiment (VADER)μ -0.028 ± 0.508
min -0.999max 0.999
low 33%medium 34%high 33%
Sentiment (TextBlob)μ 0.038 ± 0.249
min -1max 1
low 26%medium 41%high 33%
Subjectivity (TextBlob)37.4% true
true 37.4%false 62.6%
Toxicity (ToxiGen)μ 0.161 ± 0.307
min 0.001max 0.992
low 33%medium 34%high 33%
8.4
Flesch–Kincaid grade
US school grade level
9.2
Automated readability index
Frequent terms
peoplelikegamergatedonredditgamethinkpostgamesmediaknowwantvideogoodtimesjwrightwomengamingtwittergoingnewkotakuinactionwayarticleactuallyshitkiasurethingsthingsjwscommunityneeddoesnvoatpointethicsantisaidbadgotdidnfreeisnusesocialrealgawkercensorship
Topic clusters

Topic 0

think
like
yeah
fuck
sure
good
day
people

Topic 1

game
play
video
gamer
gaming
like
character
want

Topic 2

reddit
voat
kia
pao
post
mod
sub
ban

Topic 3

gamergate
kotakuinaction
medium
community
freedom
moderator
current
discussion

Topic 4

sjw
people
think
racist
social
white
like
thing

Topic 5

clinton
news
trump
times
cnn
york
journalism
campaign

Topic 6

woman
feminist
man
feminism
think
gender
like
people

Topic 7

gawker
hogan
hulk
denton
sex
lawsuit
million
trial

Topic 8

twitter
suspend
censorship
account
google
ideas
tweet
reddit
Top hashtags
#gamergate166
#kotakuinaction69
#selection28
#116
#areyoublocked9
#gg8
#stopcisa7
#cisa6
#ggatnatsucon5
#notyourshield5
#spjairplay5
#zachattack5
#24
#brokensyndicate4
#opskynet4
#oscon4
#43
#burgersandfries3
#ethics3
#fe3
Top emoji
💙1
💜1
😎1

Computed over the full corpus. Degree assortativity: exact — Pearson correlation of total degree over every edge (DuckDB) Bridge bottleneck count: exact — biconnected components of the undirected graph (NetworKit) Connected components: exact — weakly connected components (NetworKit) Density: exact Reciprocity rate: exact (DuckDB) Top 10 centrality hubs: exact — full degree count (DuckDB)

Record

Catalog key
madoc-voat-KotakuInAction
Authors
Dankulov, Marija Mitrović; Tomašević, Aleksandar; Maletić, Slobodan; Anđelković, Miroslav; Vranić, Ana; Cvetković, Darja; Stupovski, Boris; Vudragović, Dušan; Major, Sara; Bogojević, Aleksandar
Year
2025
Source paper
MADOC: Multi-Platform Aggregated Dataset of Online Communities
DOI / arXiv
10.1609/icwsm.v19i1.35954
License
Creative Commons Attribution 4.0 International (CC BY 4.0) (CC-BY-4.0)
Records
7,853
Nodes
1,878
Edges
3,854 (directed)
Nodes are
user
Edges are
reply
Attributes
nodes have no attributes; edges have no attributes
Text corpus
post text
Languages
en
Collected
2012 to 2024 (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/15690964 link checked
Hosted copy
Mirrored on echo.directory on 2026-10-02, 1.9 MB across 1 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{dankulov2025madoc,
  title   = {{MADOC: Multi-Platform Aggregated Dataset of Online Communities}},
  author  = {Dankulov, Marija Mitrović and Tomašević, Aleksandar and Maletić, Slobodan and Anđelković, Miroslav and Vranić, Ana and Cvetković, Darja and Stupovski, Boris and Vudragović, Dušan and Major, Sara and Bogojević, Aleksandar},
  journal = {Proceedings of the International AAAI Conference on Web and Social Media (ICWSM)},
  volume  = {19},
  year    = {2025},
  doi     = {10.1609/icwsm.v19i1.35954}
}

APA

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

Dankulov, M. M., Tomašević, A., Maletić, S., Anđelković, M., Vranić, A., Cvetković, D., Stupovski, B., Vudragović, D., Major, S., & Bogojević, A. (2025). MADOC: Voat / KotakuInAction [Data set]. https://doi.org/10.1609/icwsm.v19i1.35954

MLA

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

Dankulov, Marija Mitrović, et al. MADOC: Voat / KotakuInAction. 2025, doi.org/10.1609/icwsm.v19i1.35954.

BibTeX · RIS · CSL-JSON

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