Pushshift Reddit — 2014-11

A Reddit (Pushshift archive, 2014-11) dataset of 41,921,938 comments and 23,606,756 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains directed reply graph, 41,912 subreddits, content metrics: score, controversiality, gilded. Monthly slice of the Pushshift Reddit corpus for 2014-11 — full comment text, reply graph, and engagement metrics across 41,912 subreddits.. Suitable for longitudinal Reddit analysis, reply network structure, community detection, sentiment analysis, engagement research.

#Controversiality#Monthly snapshot#Pushshift#Reply network#Subreddit

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Analytics

The interactive network needs JavaScript.

· graph.json

The full graph has 41,921,938 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.

41.9M
Nodes
23.6M
Edges
1.00e-08
Density
18.3M
Components
0.01351
Assortativity
0.0%
Reciprocity
23.6M
Bridges
Most central nodes
cm5hdgb2e-05
cm6c3o52e-05
cmgmmsh1e-05
clzm8t71e-05
clu14fx1e-05
cm9ziio1e-05
cm8pfyt1e-05
cm4xnl61e-05
cmckdpl1e-05
cm4tp7g1e-05
Content metrics

41,921,938 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

scoreμ 5.671 ± 48.54
min -1.1Kmax 26.1K
controversiality0.0% true
true 0.0%false 100.0%
gildedμ 0 ± 0.069
min 0max 416
6.4
Flesch–Kincaid grade
US school grade level
6.8
Automated readability index
Frequent terms
likedonpeoplethinkgoodtimeknowwantwaygoinggamegotrightneedbetteruseprobablynewsureprettyworkloveactuallydoesnthinglotdidnlookgreatampthanksthingsbestyeahsaidfeelshitplaypostisndaymanpointtrymaybefindyearheardyearsbad
Topic clusters

Topic 0

thank
halloween
look
car
costume
like
good
dress

Topic 1

team
player
game
play
win
good
season
year

Topic 2

time
use
app
code
phone
file
ign
need

Topic 3

eat
drink
food
like
good
relapse
day
alcohol

Topic 4

game
play
level
weapon
damage
use
spell
like

Topic 5

think
know
yeah
right
point
sure
want
year

Topic 6

movie
watch
episode
video
like
series
horror
good

Topic 7

people
woman
downvote
think
rape
man
like
post

Topic 8

vote
people
government
religion
russia
believe
thing
country

Topic 9

pay
money
price
sell
account
credit
bank
worth

Topic 10

hear
probably
song
album
band
listen
music
sound
Top hashtags
#009152
#p56
#155
#or38
#sfw38
#wiki_35
#225
#973319
#323218
#t17
#315
#414
#gamergate13
#511
#973411
#98
#207
#gid6
#wiki_36
#125
Top emoji
🔥12
😊10
🔫6
🍩4
🎵4
🎃3
😂3
😉3
😏3
😁2
😍2
😜2
😢2
😭2
🐒1

Sampled: text metrics from 50K of 40.2M 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-2014-11
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
41,921,938
Nodes
41,921,938
Edges
23,606,756
Nodes are
comment
Edges are
reply
Attributes
nodes have no attributes; edges have no attributes
Text corpus
comment text
Languages
en
Collected
2014-11 (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, 4.3 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 — 2014-11 [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 — 2014-11. 2020, doi.org/10.1609/icwsm.v14i1.7347.

BibTeX · RIS · CSL-JSON

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