TBBT: r/sanctionedsuicide Ban Intervention (2018)

A Reddit (r/sanctionedsuicide ban intervention, 2018) dataset of 27,002 pre-ban posts from banned community, 142,493 pre-ban control posts, 52,442 post-ban control posts, collected by Cerulli et al. via Reddit API (ICWSM 2026). Each record contains comment ID, selftext (post body), author (pseudonymized), subreddit, score, created_utc, split label (in-before/out-before/out-after). TBBT r/sanctionedsuicide: pre- and post-ban Reddit dataset from The Big Ban Theory — standardized 3-month window around the 2018 moderation intervention with matched control communities. Suitable for content moderation effects, community migration, deplatforming research, pre/post intervention analysis, Reddit ban studies.

#Control group#Intervention study#Subreddit ban#Suicide#The big bang theory

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Analytics

The interactive network needs JavaScript.

· graph.json

The full graph has 14,198 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.

14.2K
Nodes
28.1K
Edges
1.40e-04
Density
1
Components
-0.311
Assortativity
0.0%
Reciprocity
7.7K
Bridges
Most central nodes
SanctionedSuicide0.04107
AskReddit0.01021
TimeToGo0.00782
TrueSanctionedSuicide0.00761
depression0.00747
SuicideWatch0.00669
antinatalism0.00535
pics0.0043
2meirl4meirl0.00345
gaming0.00317
Content metrics

221,937 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

scoreμ 3.652 ± 28.91
min -460max 5.3K
is banned12.2% true
true 12.2%false 87.8%
is pre ban76.4% true
true 76.4%false 23.6%
is post ban23.6% true
true 23.6%false 76.4%
6.5
Flesch–Kincaid grade
US school grade level
6.6
Automated readability index
Frequent terms
peopledonlikelifethinkwantknowsuicidefeelwaytimegoodthingsdiegoingbetterdeathrightneedlivethingfindhelpsuretrypersondoesnmaybeendyearsworkshitlotkillactuallyworldlongprobablypaindidnbadyeahgothopepointdayfuckcaresorrysaid
Topic clusters

Topic 0

drug
like
work
try
people
think
depression
therapist

Topic 1

people
life
like
thing
think
human
god
know

Topic 2

post
hotel
time
read
talk
find
send
ask

Topic 3

die
hang
death
jump
pain
rope
instinct
painful

Topic 4

suicide
people
suicidal
commit
think
life
society
want

Topic 5

fuck
troll
sub
post
lol
laugh
subreddit
shit

Topic 6

job
work
pay
money
education
college
homeless
live

Topic 7

family
parent
mother
mom
feel
know
child
dad

Topic 8

thank
share
welcome
post
read
check
interesting
glad

Topic 9

nembutal
bottle
bitcoin
custom
scam
handbook
peaceful
pill

Topic 10

hope
feel
luck
good
peace
wish
happy
thank
Top hashtags
#325
#120
#416
#214
#yodo4
#photo2
#269831
#511
#bornwithdeathsentences1
#ddmp2_cocktail1
#gs1
#overdose1
#selection1
#suicide_risk1
#thestruggle1
#time_to_death1
#v1
Top emoji
💜770
😂119
🔥100
🤣65
🖕51
💚50
👁35
💋35
👅17
👻15
👏14
😭11
🚣11
💝10
😆10

Computed over the full corpus.

Record

Catalog key
tbbt-2018-sanctionedsuicide
Authors
Cerulli, Aldo; Cima, Lorenzo; Tessa, Benedetta; Tardelli, Serena; Cresci, Stefano
Year
2026
Source paper
The Big Ban Theory: A Pre- and Post-Intervention Dataset of Online Content Moderation Actions
DOI / arXiv
10.1609/icwsm.v20i1.42780
License
CC BY-NC-ND 4.0 (CC-BY-NC-ND-4.0)
Records
221,937
Nodes
14,198
Edges
28,134 (directed)
Attributes
nodes have no attributes; edges have no attributes
Languages
en
Collected
2018 (3 months pre/post ban) (2010s)
Tasks
From the graph: link prediction, community detection
Region
Global (inferred: the platform is used worldwide)

Provenance

Originally published at
https://zenodo.org/records/18245670 link checked
Hosted copy
Mirrored on echo.directory on 2026-10-21, 187.6 MB across 3 files. Checksums in MANIFEST.json.

Citations

The Big Ban Theory: A Pre- and Post-Intervention Dataset of Online Content Moderation Actions
Aldo Cerulli, Lorenzo Cima, Benedetta Tessa, S. Tardelli, Stefano Cresci
Journal Article · Proceedings of the International AAAI Conference on Web and Social Media · 2026

4
citations
few citations so far
0
influential citations
0% of all citations

Cited by

Citation data from Semantic Scholar, retrieved 2026-10-22.

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}
}

@article{Cerulli_2026,
  title     = {The Big Ban Theory: A Pre- and Post-Intervention Dataset of Online Content Moderation Actions},
  volume    = {20},
  issn      = {2162-3449},
  url       = {http://dx.doi.org/10.1609/icwsm.v20i1.42780},
  doi       = {10.1609/icwsm.v20i1.42780},
  number    = {1},
  journal   = {Proceedings of the International AAAI Conference on Web and Social Media},
  publisher = {Association for the Advancement of Artificial Intelligence (AAAI)},
  author    = {Cerulli, Aldo and Cima, Lorenzo and Tessa, Benedetta and Tardelli, Serena and Cresci, Stefano},
  year      = {2026},
  month     = May,
  pages     = {2756–2767}
}

APA

Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory

Cerulli, A., Cima, L., Tessa, B., Tardelli, S., & Cresci, S. (2026). TBBT: r/sanctionedsuicide Ban Intervention (2018) [Data set]. https://doi.org/10.1609/icwsm.v20i1.42780

MLA

Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.

Cerulli, Aldo, et al. TBBT: r/sanctionedsuicide Ban Intervention (2018). 2026, doi.org/10.1609/icwsm.v20i1.42780.

BibTeX · RIS · CSL-JSON

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