Pushshift Reddit — 2014-06

A Reddit (Pushshift archive, 2014-06) dataset of 36,698,502 comments and 20,224,337 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 36,696 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2014-06 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 36,696 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

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· graph.json

The full graph has 36,698,502 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.

36.7M
Nodes
20.2M
Edges
2.00e-08
Density
16.5M
Components
-0.00361
Assortativity
0.0%
Reciprocity
20.2M
Bridges
Most central nodes
cieuaui0.00029
cij7xay0.00019
cihgwmn0.00013
cifwpyc0.00012
ciix6339e-05
cifnqce8e-05
cihghim8e-05
cigkued5e-05
cifnh0a5e-05
cihg9ue4e-05
Content metrics

36,698,502 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

scoreμ 5.634 ± 46.41
min -2.5Kmax 6K
controversiality2.2% true
true 2.2%false 97.8%
gildedμ 0 ± 0.021
min 0max 12
6.4
Flesch–Kincaid grade
US school grade level
6.8
Automated readability index
Frequent terms
likedonpeoplethinktimegoodknowgamewantwaygoingrightgotneedprettyusebettersurelotthingdidnactuallyworkthingsgreatdoesnnewlookthanksprobablysaidloveplaypostfeelbesttrydayfindisnyeahbadyearsshitmaybepointmangettinglittlelong
Topic clusters

Topic 0

eat
drink
drug
food
like
taste
day
good

Topic 1

look
like
skin
beard
picture
hair
color
eye

Topic 2

team
player
game
play
fan
win
good
year

Topic 3

game
play
server
wow
mmo
player
time
level

Topic 4

government
people
god
religion
law
think
christian
believe

Topic 5

movie
watch
film
episode
video
good
scene
like

Topic 6

woman
feel
man
sex
like
think
rape
people

Topic 7

doge
pay
buy
dogetipbot
money
sell
coin
loan

Topic 8

think
know
sorry
ask
question
idea
answer
want

Topic 9

car
bike
door
drive
road
water
wheel
solar

Topic 10

fuck
joke
laugh
funny
kid
shit
hilarious
sad

Topic 11

cpu
drive
monitor
card
motherboard
ram
gpu
cooler
Show all 19 topics

Topic 12

damage
deck
weapon
crit
armor
play
attack
good

Topic 13

sound
song
album
music
listen
band
like
hear

Topic 14

post
link
comment
moderator
remove
automatically
question
automoderator

Topic 15

time
month
try
year
hour
wait
week
june

Topic 16

thank
tip
appreciate
reply
awesome
add
answer
helpful

Topic 17

tsm
team
clg
play
win
lane
game
player

Topic 18

good
awesome
cool
wow
nice
pretty
great
haha
Top hashtags
#009152
#973344
#or29
#sfw29
#973426
#125
#wiki_22
#t19
#s16
#215
#37
#47
#movieguide_stars7
#wiki_rules7
#56
#gid6
#ratings6
#wiki_35
#wiki_how_to_stay_safe5
#yesallwomen5
Top emoji
😍10
🌛4
👍4
🚀4
😄2
😜2
😭2
🌝1
🐳1
😂1
😉1
😊1
😋1
😖1
😬1

Sampled: text metrics from 50K of 35.1M 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-2014-06
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
36,698,502
Nodes
36,698,502
Edges
20,224,337
Nodes are
user
Edges are
reply
Attributes
nodes have no attributes; edges have no attributes
Text corpus
comment text
Languages
en
Collected
2014-06 (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, 3.9 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 — 2014-06 [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 — 2014-06. 2020, doi.org/10.1609/icwsm.v14i1.7347.

BibTeX · RIS · CSL-JSON

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