MADOC: Reddit / pics

A MADOC (Reddit, pics) dataset of 3,453,264 users and 15,863,415 reply edges from 51,914,975 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). FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Suitable for social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.

#Madoc#Reply network#Toxigen#Vader

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Analytics

The interactive network needs JavaScript.

· graph.json

The full graph has 3,453,264 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.

3.5M
Nodes
15.9M
Edges
1.33e-06
Density
7.5K
Components
-0.01063
Assortativity
0.0%
Reciprocity
1.6M
Bridges
Most central nodes
7ccc6faa-9eed-5297-ad15-ec0e65d246190.04448
84dc96d3-6a94-543b-8b0b-f8b4efc3ba890.02116
7d0d11b2-3caf-5f42-8ebc-489eac1adc730.01235
1fb20bd0-7e64-5331-845c-5141fdbca1790.01199
58c50a27-ddf3-559d-80b6-e8c736cafa370.01152
5a1e04b6-1876-5d0a-bb86-ab76bcb89de70.01125
ebe29338-31bf-5800-ab2a-4a2a2b2acf310.00897
dadd5cdd-3bf1-557e-90c0-7533a1e21f850.00777
1681dc6a-4dca-5810-a753-98ab818ba6310.00711
f7c58912-c182-55c5-ac5f-574c04aa02a90.00624
Content metrics

51,917,058 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

Sentiment (VADER)μ 0.075 ± 0.45
min -1max 1
low 26%medium 41%high 33%
Sentiment (TextBlob)μ 0.079 ± 0.288
min -1max 1
low 20%medium 47%high 33%
Subjectivity (TextBlob)36.8% true
true 36.8%false 63.2%
Toxicity (ToxiGen)μ 0.139 ± 0.301
min 0.001max 0.993
low 33%medium 34%high 33%
5.9
Flesch–Kincaid grade
US school grade level
6.3
Automated readability index
Frequent terms
likepeopledongoodknowthinktimelooknewyearrightlookswayyearsworkpictureactuallygotwantprettygoingthingdaygreatmansureshitbetterguyfuckdidndoesnlotneeddogprobablypostyeahthoughtredditbestconformlovelittleyesthingslifeusebadfucking
Topic clusters

Topic 0

new
year
happy
years
eve
christmas
resolution
day

Topic 1

upvote
fuck
downvote
karma
post
reddit
repost
comment

Topic 2

water
surface
tension
tree
beach
ocean
snow
rock

Topic 3

picture
camera
photo
pic
art
post
image
exposure

Topic 4

look
face
like
titty
boob
girl
color
makeup

Topic 5

chipotle
burger
lobster
eat
cheese
biscuit
bacon
red

Topic 6

yeah
yep
sure
true
right
woah
yea
actually

Topic 7

rhino
horn
poacher
chinese
china
animal
poach
kill

Topic 8

kidney
transplant
dialysis
year
recovery
surgery
friend
luck

Topic 9

dog
leash
friendly
owner
people
bite
walk
park

Topic 10

sniper
gun
burn
shot
sign
fire
hand
shoot

Topic 11

think
guess
word
hear
thought
real
talk
read
Show all 43 topics

Topic 12

play
game
tip
steal
jag
force
tap
metric

Topic 13

tilt
package
ship
box
fedex
indicator
shipping
delivery

Topic 14

card
phone
computer
storage
drive
flash
microsd
memory

Topic 15

weed
drug
dispensary
legal
smoke
marijuana
colorado
ounce

Topic 16

uncle
phil
james
avery
prince
rip
fresh
paul

Topic 17

buy
pay
price
dollar
tax
store
minimum
cash

Topic 18

walmart
mart
wal
employee
work
woman
attractive
hot

Topic 19

cool
nice
beautiful
awesome
pretty
amazing
gorgeous
brilliant

Topic 20

luck
shaq
good
hope
wish
god
prayer
friend

Topic 21

thank
share
sir
appreciate
yoo
bravo
input
generous

Topic 22

car
nissan
micra
look
honda
suv
paint
like

Topic 23

dog
service
animal
flight
plane
allow
support
travel

Topic 24

apple
door
store
logo
glass
cover
repair
employee

Topic 25

dick
backwards
guy
penis
draw
fap
gay
think

Topic 26

oil
chrysler
engine
mile
car
change
wrangler
motor

Topic 27

dui
lawyer
cab
drunk
drive
driver
court
cost

Topic 28

plane
fly
flight
pilot
airplane
airline
museum
air

Topic 29

time
watch
minute
alien
spaceship
interval
fps
listen

Topic 30

drunk
drink
hangover
beer
night
liquor
drinking
cider

Topic 31

moon
dogecoin
doge
dogetipbot
shibe
wallet
coin
tip

Topic 32

hospital
insurance
pay
cover
bill
medical
cost
health

Topic 33

kill
soviet
woman
war
sniper
combat
russian
stalin

Topic 34

smell
clean
bathroom
pee
piss
toilet
floor
handler

Topic 35

girl
ukulele
bang
jizz
believe
little
banjo
sing

Topic 36

guy
friend
dude
ursula
man
buddy
hot
ice

Topic 37

joke
laugh
funny
satire
hilarious
humor
laughter
bad

Topic 38

brain
creepy
fear
injure
scared
injury
terrifying
bastard

Topic 39

video
link
youtube
click
watch
music
commercial
talk

Topic 40

dad
father
die
celebrity
smith
dadjoke
actor
death

Topic 41

line
try
queue
long
rope
raid
attempt
roll

Topic 42

forget
cry
tear
spoiler
lou
reed
forgot
damn
Top hashtags
#323224
#t20
#117
#28
#47
#95
#facrc5
#singularity5
#yolo4
#103
#53
#83
#02
#62
#biv2
#da2
#death2
#deep2
#energy_densities_of_common_energy_storage_materials2
#hero_fortress2
Top emoji
🌚35
👍2
😉2
𝟤1
🍌1
🎉1
🐬1
👴1
💭1
😊1
😏1
😕1
😝1

Sampled: text metrics from 50K of 51.9M records; topic model from 20K. 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-reddit-pics
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
51,914,975
Nodes
3,453,264
Edges
15,863,415 (directed)
Nodes are
user
Edges are
reply
Attributes
nodes have no attributes; edges have no attributes
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, 8.2 GB 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: Reddit / pics [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: Reddit / pics. 2025, doi.org/10.1609/icwsm.v19i1.35954.

BibTeX · RIS · CSL-JSON

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