Pushshift Reddit — 2013-01

A Reddit (Pushshift archive, 2013-01) dataset of 25,387,945 comments and 12,711,665 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 23,503 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2013-01 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 23,503 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.

#Comment tree#Pushshift#Reply network#Subreddit

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Analytics

The interactive network needs JavaScript.

· graph.json

The full graph has 25,387,945 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.

25.4M
Nodes
12.7M
Edges
2.00e-08
Density
12.7M
Components
0.00283
Assortativity
0.0%
Reciprocity
12.7M
Bridges
Most central nodes
c7vj0ij3e-05
c7wnp373e-05
c7xxo3e2e-05
c80kvpw2e-05
c7s2iwg2e-05
c83sbdr2e-05
c809xie2e-05
c7w3rwz2e-05
c854rlo2e-05
c7wj9vb2e-05
Content metrics

25,387,945 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

scoreμ 5.741 ± 42.03
min -1.8Kmax 4.7K
controversiality0.1% true
true 0.1%false 99.9%
gildedμ 0 ± 0.016
min 0max 22
6.3
Flesch–Kincaid grade
US school grade level
6.7
Automated readability index
Frequent terms
likedonpeoplethinktimegoodknowwantnewwayusagoinggameyearrightgotbetterneedthinguseactuallyprettydidnsuredoesnyearslotgreatlookworkthingslovesaiddayprobablythanksfindbestfeelguybadtrypointlittleplayisnpostshitmanwat
Topic clusters

Topic 0

drink
eat
smoke
tea
bottle
beer
taste
flavor

Topic 1

look
dog
wear
shoe
like
hair
fit
color

Topic 2

team
game
season
year
win
playoff
play
fan

Topic 3

new
year
happy
years
night
tonight
eve
party

Topic 4

car
snow
drive
road
bike
bag
ride
walk

Topic 5

woman
relationship
sex
like
want
thing
think
man

Topic 6

music
song
band
album
metal
sound
listen
like

Topic 7

card
newegg
usb
cpu
monitor
run
code
laptop

Topic 8

play
team
game
lane
damage
kill
deck
pick

Topic 9

video
movie
watch
episode
film
favorite
scene
youtube

Topic 10

link
post
click
edit
browser
thread
reddit
google

Topic 11

thank
appreciate
awesome
lot
yes
headphone
share
praise
Show all 29 topics

Topic 12

iphone
sell
phone
buy
ipad
nexus
sale
price

Topic 13

good
amazing
awesome
luck
hope
cool
wow
pretty

Topic 14

game
play
time
guild
like
character
feel
fun

Topic 15

try
time
start
month
day
hour
hop
late

Topic 16

fuck
bitch
fucking
bad
suck
stupid
motherfucker
shut

Topic 17

tax
government
social
pay
vote
security
money
country

Topic 18

god
religion
church
faith
religious
people
believe
atheism

Topic 19

karma
upvote
downvote
post
repost
vote
reddit
whore

Topic 20

think
know
explain
thought
mean
understand
knowledge
yeah

Topic 21

yes
desu
sure
right
agree
sir
definitely
exactly

Topic 22

que
spanish
los
accent
english
translate
gott
french

Topic 23

gun
firearm
law
amendment
weapon
ban
assault
war

Topic 24

picture
paint
lens
photo
photoshop
draw
camera
use

Topic 25

laugh
joke
funny
hilarious
comedian
audience
hard
camp

Topic 26

fight
guy
punch
martial
defend
hit
art
situation

Topic 27

school
class
teacher
college
high
student
university
course

Topic 28

troll
people
hate
child
argue
offend
childfree
stupid
Top hashtags
#171
#323244
#242
#973437
#auto28
#t28
#973323
#010
#310
#48
#58
#396
#s5
#v5
#94
#914
#934
#fn4
#123
#more3
Top emoji
👽1

Sampled: text metrics from 50K of 24.4M 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
pushshift-reddit-2013-01
Authors
Baumgartner, Jason; Zannettou, Savvas; Keegan, Brian; Squire, Megan; Blackburn, Jeremy
Year
2020
Source paper
The Pushshift Reddit Dataset
DOI / arXiv
10.1609/icwsm.v14i1.7347
License
Unknown
Records
25,387,945
Nodes
25,387,945
Edges
12,711,665
Nodes are
user
Edges are
reply
Attributes
nodes have no attributes; edges have no attributes
Text corpus
comment text
Languages
en
Collected
2013-01 (2010s)
Tasks
From the graph: link prediction, community detection
Region
Global (inferred: the platform is used worldwide)

Provenance

Originally published at
https://files.pushshift.io/reddit/comments/ unverified
Hosted copy
Mirrored on echo.directory on 2026-10-02, 2.6 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}
}

@misc{baumgartner2020pushshift,
  title         = {The Pushshift Reddit Dataset},
  author        = {Baumgartner, Jason and Zannettou, Savvas and Keegan, Brian and Squire, Megan and Blackburn, Jeremy},
  year          = {2020},
  eprint        = {2001.08435},
  archiveprefix = {arXiv}
}

APA

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

Baumgartner, J., Zannettou, S., Keegan, B., Squire, M., & Blackburn, J. (2020). Pushshift Reddit — 2013-01 [Data set]. https://doi.org/10.1609/icwsm.v14i1.7347

MLA

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

Baumgartner, Jason, et al. Pushshift Reddit — 2013-01. 2020, doi.org/10.1609/icwsm.v14i1.7347.

BibTeX · RIS · CSL-JSON

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