Pushshift Reddit — 2014-05

A Reddit (Pushshift archive, 2014-05) dataset of 37,099,033 comments and 20,261,974 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains directed reply graph, 37,502 subreddits, content metrics: score, controversiality, gilded. Monthly slice of the Pushshift Reddit corpus for 2014-05 — full comment text, reply graph, and engagement metrics across 37,502 subreddits.. Suitable for longitudinal Reddit analysis, reply network structure, community detection, sentiment analysis, engagement research.

#Comment tree#Pushshift#Reply network#Subreddit

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Analytics

The interactive network needs JavaScript.

· graph.json

The full graph has 37,099,033 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.

37.1M
Nodes
20.3M
Edges
1.00e-08
Density
16.8M
Components
0.00106
Assortativity
0.0%
Reciprocity
20.3M
Bridges
Most central nodes
chg3orh5e-05
chfi9ik2e-05
chq6lsp2e-05
chex9eq2e-05
chi5pnl2e-05
chk21fm2e-05
chaxr0o1e-05
cho7uo41e-05
ch9yurl1e-05
chlqrod1e-05
Content metrics

37,099,033 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

scoreμ 5.641 ± 45.62
min -1.3Kmax 8.7K
controversiality2.3% true
true 2.3%false 97.7%
gildedμ 0 ± 0.025
min 0max 71
6.4
Flesch–Kincaid grade
US school grade level
6.8
Automated readability index
Frequent terms
likedonpeoplethinkknowtimegoodwantwaygamegoingrightgotneeduseprettysureworkbetterdoesnthingactuallylotdidnlookthingsloveprobablygreatsaidnewthanksfeelshitdaybestfindbadpostyeahtryyearsmanplayisnmaybepointfuckgettinglittle
Topic clusters

Topic 0

team
play
player
game
win
season
year
goal

Topic 1

look
hair
like
awesome
shoe
wear
love
face

Topic 2

fuck
hate
fucking
guy
man
bitch
shit
bad

Topic 3

water
beer
drink
eat
taste
bottle
juice
coffee

Topic 4

feel
woman
sex
relationship
man
want
people
like

Topic 5

damage
deck
weapon
game
level
play
player
armor

Topic 6

music
song
sound
album
listen
genre
track
post

Topic 7

thank
appreciate
check
feedback
man
helpful
cool
help

Topic 8

god
people
religion
black
racist
church
think
believe

Topic 9

car
bike
drive
lane
speed
truck
road
turn

Topic 10

cpu
core
laptop
server
download
app
file
run

Topic 11

school
job
pay
year
tax
work
wage
student
Show all 30 topics

Topic 12

price
sell
buy
money
card
bitcoin
market
cost

Topic 13

smile
happy
good
nice
perfect
fine
grin
day

Topic 14

time
minute
start
late
hour
luck
tomorrow
charleston

Topic 15

vote
party
candidate
government
majority
seat
primary
obama

Topic 16

game
play
mario
wii
xbox
release
bundle
console

Topic 17

clg
team
laner
mid
lane
link
lcs
mana

Topic 18

question
ask
know
answer
point
curious
wonder
interested

Topic 19

episode
season
character
spider
anime
story
superman
peter

Topic 20

joke
laugh
funny
hilarious
giggle
think
comedian
read

Topic 21

movie
watch
video
film
youtube
good
documentary
think

Topic 22

breed
hat
hand
leg
horse
male
glass
hole

Topic 23

read
wrong
comment
fiction
book
story
write
typo

Topic 24

automatically
moderator
submission
automoderator
concern
contact
perform
question

Topic 25

yes
right
sure
yeah
correct
yup
jedi
yep

Topic 26

dog
cat
animal
pet
human
vet
kitty
abuse

Topic 27

think
mind
thought
mean
yea
poo
reasoning
genius

Topic 28

death
murder
die
torture
people
justice
crime
kill

Topic 29

upvote
reddit
downvote
karma
repost
post
upvoted
subreddit
Top hashtags
#009111
#or37
#sfw37
#135
#t23
#973315
#wiki_13
#wiki_rules13
#211
#i10
#wiki_mods9
#32328
#06
#36
#46
#x276
#97345
#quick5
#go4
#hotfix4
Top emoji
😍15
😢4
😊2
👉1
👌1
😁1
😂1
😤1
😨1
😱1
😳1

Sampled: text metrics from 50K of 35.5M 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-2014-05
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
37,099,033
Nodes
37,099,033
Edges
20,261,974
Nodes are
comment
Edges are
reply
Attributes
nodes have no attributes; edges have no attributes
Text corpus
comment text
Languages
en
Collected
2014-05 (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, 4.0 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 — 2014-05 [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 — 2014-05. 2020, doi.org/10.1609/icwsm.v14i1.7347.

BibTeX · RIS · CSL-JSON

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