Decentralized Moderation Audit Log

This dataset provides a detailed, transparent audit log of decentralized content moderation actions across distributed nodes on social media platforms. It tracks moderation events, policy adherence, and review speed, enabling compliance officers and platform managers to analyze moderation effectiveness, consistency, and integrity in decentralized environments.

  • last updated 23 Jan 2026
  • by GoMask
The brief that made it

Compliance auditing and reporting for decentralized moderation processes

Sample rows

preview · 8 of 121 rows · all 18 columns
audit_log_idstringmoderation_actionstringreview_duration_secondsintegeris_automatedbooleannode_location_countrystringaction_timestampdatetimenode_idstringmoderator_idstringcontent_idstringcontent_typestringuser_idstringpolicy_idstringaction_statusstringflag_countintegernode_location_citystringcontent_created_timestampdatetimepolicy_descriptionstringaction_reasonstring
cA9fK3-jP4z2TQ8dremove302falseUnited States2024-05-15T09:38:12Znode-US-102mod-jackson-12image-1001imageuser7852pol-hate-21completed3Chicago2024-05-15T09:30:02ZRemoval due to violation of hate speech guidelines.Content contained explicit hateful language targeting a community.
e4b9b6d0-7f12-4e2c-acd9-15f7bbdaflag2trueIndia2024-04-18T16:08:41Znode-IN-207auto-ml-102post-2002postuser4321pol-spam-08completed7Bangalore2024-04-18T16:07:59ZAutomated flagging for spam content.Detected multiple repeated links characteristic of spam.
A7dEKM3dapprove0falseGermany2024-03-21T13:14:50Znode-DE-034mod-anna-81comment-3098commentuser1123pol-gen-11completed0Berlin2024-03-21T13:14:40ZRoutine approval for compliant comment.Comment reviewed and found to follow all community guidelines.
4f9d3baf-348a-4e1c-8ec6-8a22a9a1e63awarn1trueUnited Kingdom2024-06-01T17:10:27Znode-UK-021auto-nn-77post-2487postuser5467pol-offtopic-04pending2London2024-06-01T17:09:58ZAutomated warning for off-topic discussion.Content detected as off-topic in reference to the original thread.
c0f42d9b-2a2d-4f5d-ae2a-2d3e9fcdrestrict2falseSouth Africa2024-02-19T08:21:15Znode-ZA-057mod-thabo-51profile-5812profileuser3432pol-age-05pending0Cape Town2024-02-19T08:18:23ZblankProfile restricted pending age verification.
6b2c1a8e-9332-4e32-bd8d-a2e5f8a7restore671falseFrance2024-04-09T21:04:13Znode-FR-045mod-marcel-19image-1209imageuser9977pol-appeal-04completed5Paris2024-04-09T17:52:01ZRestoration following successful appeal.User appealed and provided evidence of compliance.
b2a3e8c2flag0trueCanada2024-05-09T11:24:08Znode-CA-019auto-edge-14comment-4010commentuser5634pol-spam-17completed4Toronto2024-05-09T11:23:41ZFlagged for spam-like behavior by automated filter.Multiple identical comments detected across threads.
f9d4bf32-6fcd-4e2d-8b31-1b8e4b22c1f0warn3trueArgentina2024-03-28T19:40:36Znode-AR-008auto-ml-55post-2934postuser2100pol-abuse-09pending1Buenos Aires2024-03-28T19:40:22ZAutomated warning for abusive language.Potentially abusive language detected by NLP engine.

What the 121 rows show

from the 121-row sample

Restore (moderation action) stands out: mean review_duration_seconds is 728.1, against 77.9 for the rest.

  • 32%is_automated = true
  • 2median review_duration_seconds
  • 4action statuses
  • 6content types
  • 2median flag_count
Mean review_duration_seconds by moderation_action121 rows
0400800310.6remove27 rows1.6flag24 rows1.4appro…22 rows1.3warn15 rows0.76restr…21 rows728.1resto…12 rows
review_duration_seconds121 rows, in bands of 200
050100966386206001,200review_duration_seconds →

Median 2, from 0 to 1,008.

node_location_country113 rows with a value · 8 left blank
  1. United States12
  2. Germany8
  3. United Kingdom8
  4. Canada8
  5. Argentina7
  6. France6
  7. Australia5
  8. India4
  9. South Africa4
  10. Russia4
18 columns by typefrom the column list below
  • string 13
  • integer 2
  • datetime 2
  • boolean 1

Columns

18 columns in four groups
blueprint · 18 columns
columntypedescriptionexample
Text 13 columns
audit_log_idstringUnique identifier for each moderation audit log entryuniquecA9fK3-jP4z2TQ8d
moderation_actionstringType of moderation action performed (e.g., remove, flag, approve, warn)6 valuesremove
node_idstringUnique identifier for the decentralized node that performed the actionnode-US-102
moderator_idstringUnique identifier for the moderator (human or automated agent)mod-jackson-12
content_idstringUnique identifier for the content item being moderatedimage-1001
content_typestringType of content (e.g., post, comment, image, video)6 valuesimage
user_idstringUnique identifier for the user who created the contentuser7852
policy_idstringIdentifier for the moderation policy or rule appliedpol-hate-21
policy_descriptionstringDescription of the moderation policy or rule appliedoptionalRemoval due to violation …
action_reasonstringReason provided for the moderation actionContent contained explici…
action_statusstringStatus of the moderation action (e.g., completed, pending, reversed)completed · pending · reversed · failedcompleted
node_location_countrystringCountry where the moderation node is locatedoptionalUnited States
node_location_citystringCity where the moderation node is locatedoptionalChicago
Numbers 2 columns
review_duration_secondsintegerTime taken (in seconds) to review and act on the content0 or more · optional302
flag_countintegerNumber of times the content was flagged prior to moderation action0 or more · optional3
Dates and times 2 columns
action_timestampdatetimeTimestamp when the moderation action was executed2024-05-15T09:38:12Z
content_created_timestampdatetimeTimestamp when the content was originally created2024-05-15T09:30:02Z
True or false 1 column
is_automatedbooleanIndicates if the moderation action was performed by an automated systemfalse

Use it for

  • is automated32%39 of 121 rowsmean review duration …310.6remo…1.6flag1.4appr…1.3warn

    A social media dashboard

    The is_automated rate, review_duration_seconds by moderation_action and a breakdown of node_location_country. Excel, Power BI or Tableau.

  • Why do the 12 restore rows have a mean review_duration_seconds of 728.1?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable audit logs with moderation_action, action_timestamp and node_id to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 18 columns, your size and your rules. See 20 rows before you pay.

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This dataset121 rows18 columns
Yours10,000 rows18 columnsnode_location_country: UK only

blueprint · decentralized-moderation-audit-log

Behind this dataset

Same schema. As many rows as you need.

These 121 rows came out of a blueprint — 18 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Each action must specify node ID and moderator role
  • Logged actions include timestamp, type, and outcome
  • Policy violations must be flagged and categorized
  • Nodes must maintain a minimum action-to-flag ratio
  • Duplicate actions across nodes are not permitted
  • All moderation actions must be traceable to their source
Rows
Open the blueprint in Data Factory

1 credit per row. New accounts start with 25 free credits.

Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
decentralized-moderation-audit-log

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