Pushshift Reddit — 2014-02

A Reddit (Pushshift archive, 2014-02) dataset of 33,496,677 comments and 17,896,141 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 34,880 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2014-02 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 34,880 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#Subreddit

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Analytics

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· graph.json

The full graph has 33,496,677 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.

33.5M
Nodes
17.9M
Edges
2.00e-08
Density
15.6M
Components
0.00742
Assortativity
0.0%
Reciprocity
17.9M
Bridges
Most central nodes
cfe3rgc3e-05
cffueio2e-05
cf9r5t61e-05
cfk45o51e-05
cf58l8v1e-05
cfntao41e-05
cfbdr641e-05
cfagmge1e-05
cf55dso1e-05
cf52ye81e-05
Content metrics

33,496,677 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

scoreμ 5.63 ± 46.58
min -1.1Kmax 28.4K
controversiality2.3% true
true 2.3%false 97.7%
gildedμ 0 ± 0.021
min 0max 17
6.4
Flesch–Kincaid grade
US school grade level
7.0
Automated readability index
Frequent terms
likedonpeoplethinkknowgoodtimewantwaygoingrightgamegotneedprettylotthingsureusebetterworkdoesnactuallydidnthingslovenewgreatlookthankssaidprobablydaytrypointfeelbestyearsplaypostyeahfindisnmaybebadlittlemanlongdifferentshit
Topic clusters

Topic 0

game
play
gun
player
kill
level
like
good

Topic 1

look
wear
like
hair
color
size
love
bra

Topic 2

movie
episode
watch
film
video
superman
think
like

Topic 3

song
album
sound
music
listen
band
hear
like

Topic 4

eat
drink
cook
food
meat
pizza
smoke
like

Topic 5

pay
job
work
month
sell
company
employee
buy

Topic 6

thank
check
appreciate
help
remind
wow
haha
add

Topic 7

team
game
fan
play
season
player
year
nba

Topic 8

trade
breed
shiny
add
pokemon
egg
interested
list

Topic 9

cpu
card
motherboard
drive
install
ram
update
newegg

Topic 10

car
engine
bike
wheel
road
gas
truck
drive

Topic 11

think
question
answer
guess
ask
maybe
know
second
Show all 26 topics

Topic 12

government
vote
military
state
party
political
country
system

Topic 13

downvote
reddit
upvote
post
comment
gold
karma
bad

Topic 14

feel
relationship
woman
sex
like
think
want
time

Topic 15

god
people
believe
gay
religion
jesus
life
church

Topic 16

fuck
fucking
shit
hate
dumb
stupid
complain
suck

Topic 17

link
leave
phone
software
post
language
operation
write

Topic 18

btc
dogecoin
coin
bitcoin
usd
doge
currency
shibe

Topic 19

funny
joke
laugh
comedy
hilarious
sarcasm
humor
giggle

Topic 20

club
player
league
sign
play
clause
signing
deal

Topic 21

time
wait
tomorrow
hour
late
minute
start
location

Topic 22

birthday
happy
nice
congrat
congratulation
good
beautiful
great

Topic 23

yes
right
yeah
sure
agree
exactly
actually
true

Topic 24

att
que
som
för
har
jag
med
till

Topic 25

dog
inch
penis
blood
ugly
anal
pain
size
Top hashtags
#009228
#146
#women31
#230
#men30
#gender28
#973327
#class23
#t23
#sex20
#39318
#man18
#cismale16
#cisfemale15
#973413
#woman13
#312
#frequent8
#privileged7
#32326
Top emoji
🎁1
👍1
💥1
💫1
😂1
😅1
😆1
😇1
😉1
😊1
😍1
😐1
😕1

Sampled: text metrics from 50K of 32M 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-2014-02
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
33,496,677
Nodes
33,496,677
Edges
17,896,141
Attributes
nodes have no attributes; edges have no attributes
Languages
en
Collected
2014-02 (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, 3.6 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 — 2014-02 [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 — 2014-02. 2020, doi.org/10.1609/icwsm.v14i1.7347.

BibTeX · RIS · CSL-JSON

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