Pushshift Reddit — 2014-10

A Reddit (Pushshift archive, 2014-10) dataset of 42,947,083 comments and 24,051,938 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 41,337 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2014-10 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 41,337 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.

#Comment tree#Monthly snapshot#Pushshift#Reply network#Subreddit

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Analytics

The interactive network needs JavaScript.

· graph.json

The full graph has 42,947,083 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.

42.9M
Nodes
24.1M
Edges
1.00e-08
Density
18.9M
Components
0.01051
Assortativity
0.0%
Reciprocity
24.1M
Bridges
Most central nodes
cl1ygat2e-05
cl4pccg2e-05
clb1cij1e-05
cl4q2sr1e-05
cl5msoh1e-05
cldxdae1e-05
cljlw4k1e-05
clb33zx1e-05
cljmrgm1e-05
clb23jw1e-05
Content metrics

42,947,083 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

scoreμ 5.558 ± 47.02
min -3.2Kmax 7.3K
gildedμ 0 ± 0.022
min 0max 23
6.5
Flesch–Kincaid grade
US school grade level
6.8
Automated readability index
Frequent terms
likedonpeoplethinkknowtimegoodwantwaygoinggamegotrightneeduseprettyworksurebetterthingactuallydoesnlotdidnprobablythingsnewthankspostlovegreatsaidfeellookdaybadplayisnbestyeahmaybeshityearsyeartrypointfindlonglittleman
Topic clusters

Topic 0

game
play
like
damage
level
player
good
time

Topic 1

team
game
player
year
trade
play
fan
think

Topic 2

eat
food
fat
like
drink
weight
calorie
day

Topic 3

look
water
toilet
wear
bidet
hair
like
paper

Topic 4

car
bike
drive
driver
look
turn
like
need

Topic 5

windows
phone
app
use
update
window
computer
screen

Topic 6

people
vote
god
religion
evidence
government
war
president

Topic 7

yes
yeah
good
awesome
wow
nice
holy
sure

Topic 8

episode
movie
video
anime
watch
character
series
book

Topic 9

song
album
sound
band
hear
listen
music
play

Topic 10

thank
appreciate
advice
awesome
alright
try
cool
man

Topic 11

post
question
moderator
automatically
remove
perform
comment
automoderator
Show all 21 topics

Topic 12

link
flair
post
search
comment
original
idea
font

Topic 13

job
work
pay
year
school
wage
hire
degree

Topic 14

ebola
africa
spread
country
disease
people
infect
outbreak

Topic 15

sell
month
price
buy
ship
sale
ebay
money

Topic 16

woman
man
people
feminism
troll
sexual
gender
post

Topic 17

kill
cop
die
fire
police
dead
burn
gun

Topic 18

joke
laugh
funny
hilarious
chuckle
think
giggle
head

Topic 19

feel
guy
mom
friend
dude
man
old
year

Topic 20

relationship
dad
cheat
friend
want
sex
marriage
kid
Top hashtags
#009105
#155
#240
#wiki_28
#422
#contributions19
#or19
#sfw19
#316
#t16
#323210
#107
#67
#97
#wiki_24_hour_limit7
#wiki_37
#06
#56
#85
#bdsm5
Top emoji
😜4
😁3
😭3
😂2
😉2
🍪1
👍1
💓1
💙1
💪1
😀1
😄1
😆1
😊1
😌1

Sampled: text metrics from 50K of 41.1M 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-2014-10
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
42,947,083
Nodes
42,947,083
Edges
24,051,938
Nodes are
user
Edges are
reply
Attributes
nodes have no attributes; edges have no attributes
Text corpus
comment text
Languages
en
Collected
2014-10 (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, 4.4 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 — 2014-10 [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 — 2014-10. 2020, doi.org/10.1609/icwsm.v14i1.7347.

BibTeX · RIS · CSL-JSON

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