DATA COLLECTION CHECKLIST

Ban Forensics Data Collection Checklist

Purpose: Exact data points to collect per banned account so the analysis model can determine which detection vectors triggered each ban. Target: Windows EC2 Hermes (has AdsPower, cookies, proxy, profile management tools) Scope: 5 banned accounts only — hailybarnes37, joycehicks2026, Key_Character6482, Ok_Bobcat9406, delilahmelendez30

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Section A: Per-Account Comment History (CRITICAL — fetch first)

For each of the 5 banned accounts, collect ALL comments from Reddit’s public API.

Fetch Method

Endpoint: GET https://www.reddit.com/user/{username}/comments.json?limit=100&sort=new&raw_json=1
Paginate: Follow "after" cursor until no more results
Transport: curl via hailybarnes37's proxy (213.201.251.213:5407, user: tyzmousa, pass: rvutibqywubn)
Cookies: hailybarnes37's cookies (from AdsPower profile or rdt-cli credential.json)
Rate: 7+ second delay between every request
Account: Fetch ONE account per session

Data Points Per Comment

#	Field	Source	Analysis Purpose
A1	comment_id	data.id	Unique identifier, dedup
A2	comment_body	data.body	Full text — check for question-back pattern, vagueness, AI tells
A3	subreddit	data.subreddit	Subreddit distribution, karma-farming cluster exposure
A4	score	data.score	Low-score clusters = content not landing
A5	created_utc	data.created_utc	Timestamp for timing analysis
A6	permalink	data.permalink	Cross-reference with ban messages, BotBouncer reports
A7	parent_id	data.parent_id	Was it top-level (t3_) or reply (t1_)?
A8	is_top_level	Derived from A7	Top-level vs reply pattern
A9	gilded	data.gilded	Awarded comments = high quality
A10	controversiality	data.controversiality	1 = upvoted AND downvoted significantly
A11	edited	data.edited	false/timestamp — did we edit? (human behavior)
A12	distinguished	data.distinguished	Mod/admin distinguished (unlikely for our accounts)
A13	num_reports	data.num_reports	How many users reported this comment (if visible)
A14	removal_reason	data.removal_reason	If removed, why?

Post Context (Fetch for each post our accounts commented on)

#	Field	Source	Analysis Purpose
A15	post_title	Fetch parent post	Did our comment match the post’s topic/intent?
A16	post_type	is_self, url, is_video	Question, discussion, image, link — did we match the type?
A17	post_subreddit	data.subreddit	Same as A3 but for cross-checking
A18	post_score	data.score	Did we comment on high/low engagement posts?
A19	post_num_comments	data.num_comments	Did we target crowded or quiet threads?
A20	post_author	data.author	Did we comment on our own swarm’s posts?

Derived Analysis Per Comment

#	Derived Field	How to Compute	Analysis Purpose
A21	ends_with_question	Check if body ends with ”?”	Question-back pattern detection
A22	word_count	len(body.split())	Length distribution per subreddit
A23	has_specific_content	Check for named items, numbers, specific references	Vagueness detection — does it name things?
A24	is_vague	Heuristic: no specific nouns, no numbers, no personal anecdotes	The BotBouncer-reported pattern
A25	has_question_back	Heuristic: answer + question to community	The exact reported pattern
A26	ai_tell_phrases	Check for “delve”, “tapestry”, “nuance”, “it’s important to remember”, “in conclusion”	AI linguistic tells
A27	time_of_day	Convert created_utc to account’s timezone	Does activity match account’s timezone?
A28	day_of_week	From created_utc	Weekday vs weekend pattern
A29	gap_from_prev_comment	created_utc - prev_comment_created_utc	Automation detection — uniform gaps = bot

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Section B: Per-Account Overview (Posts + Comments Combined)

Fetch Method

Endpoint: GET https://www.reddit.com/user/{username}/overview.json?limit=100&sort=new&raw_json=1
Paginate: Follow "after" cursor
Same transport/cookies/rate limits as Section A

Data Points

#	Field	Source	Analysis Purpose
B1	All fields from Section A (for comments)	Same	Same
B2	post_title (for submissions)	data.title	What did we post?
B3	post_body	data.selftext	Full post text
B4	post_url	data.url	Link posts — what domains did we link?
B5	is_self_post	data.is_self	Text vs link post ratio
B6	post_score	data.score	Post performance

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Section C: Account Profile (About)

Fetch Method

Endpoint: GET https://www.reddit.com/user/{username}/about.json?raw_json=1
Transport: Same proxy, logged-out (no cookies) for comparison, then logged-in (with cookies) for comparison

Data Points

#	Field	Source	Analysis Purpose
C1	total_karma	data.total_karma	Account karma at time of fetch
C2	link_karma	data.link_karma	Post karma vs comment karma ratio
C3	comment_karma	data.comment_karma	Comment-specific karma
C4	account_created_utc	data.created_utc	Account age
C5	is_suspended	data.is_suspended	Check if Reddit shows suspension flag
C6	is_verified	data.is_verified	Email verification status
C7	has_verified_email	data.has_verified_email	Email verification (CQS factor)
C8	is_gold	data.is_gold	Premium status
C9	is_mod	data.is_mod	Moderator status (unlikely)
C10	subreddit	data.subreddit.title	User profile subreddit name
C11	verified	data.verified	Verification status

Logged-Out vs Logged-In Comparison

#	Comparison	Why
C12	Fetch about.json logged-out (no cookies) via proxy	See what others see — if profile shows “suspended” or 404
C13	Fetch about.json logged-in (with hailybarnes37 cookies)	See what the account sees — banned accounts may see themselves as normal
C14	Compare C12 vs C13	If logged-in shows normal but logged-out shows suspended = shadowban/suspension

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Section D: BotBouncer Evidence (Already Collected — Verify Completeness)

Already Done ✅

• Per-username search on r/BotBouncer for all 5 accounts
• Fetched full post + comment content for 3 known BotBouncer posts
• Fetched the offending comment for hailybarnes37 (surviving)

Still Needed

#	Data Point	How to Get	Purpose
D1	Check if joycehicks2026 has a BotBouncer post	Search not found — try Google: site:reddit.com/r/BotBouncer "joycehicks2026"	May exist but not via Reddit search
D2	Check if Key_Character6482 has a BotBouncer post	Same Google search method	Same
D3	Check if Ok_Bobcat9406 has a BotBouncer post	Same Google search method	Same
D4	Check r/BotBouncer wiki for list of participating subreddits	Fetch https://www.reddit.com/r/BotBouncer/wiki/index	Know which subs have BotBouncer installed
D5	Fetch BotBouncer source: karmaFarmingSubsCheck.ts	https://github.com/fsvreddit/bot-bouncer/blob/main/src/karmaFarmingSubsCheck.ts	Get the actual list of subs BotBouncer considers karma-farming
D6	Fetch BotBouncer source: aiAnalysis/ directory	https://github.com/fsvreddit/bot-bouncer/tree/main/src/aiAnalysis	Understand what AI patterns BotBouncer checks for

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Section E: Subreddit Ban Messages (from our monitoring pipeline)

From reddit_metrics.db (if accessible on Windows EC2)

#	Data Point	Table	Purpose
E1	All subreddit bans per account	bans table	Which subs banned each account, when, and why
E2	Ban message body	bans.ban_body	The actual ban reason text from mods
E3	Offending comment permalink	bans.comment_permalink	Link to the specific comment that triggered the ban
E4	Ban status (pending/accepted)	bans.status	Whether the ban was accepted or appealed

From profile-registry.json (already have partial data)

#	Data Point	Path	Purpose
E5	karma_history snapshots	reddit.karma_history	Karma trajectory over time
E6	today_comments	reddit.today_comments	Recent comments with body_preview
E7	account status	profile.status	active/suspended/shadowbanned
E8	account creation date	reddit.account_created	Account age

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Section F: Timing & Behavioral Pattern Analysis

Compute From Section A Data

#	Analysis	How to Compute	Purpose
F1	Comments per day	Group by date(created_utc)	Burst detection — 13/day is suspicious
F2	Comments per hour	Group by hour(created_utc)	Activity time distribution
F3	Active hours vs account timezone	Compare F2 to account TZ	Does activity match the account’s supposed timezone?
F4	Day-of-week distribution	Group by weekday	Automation = uniform; human = weekend-heavy or weekday-heavy
F5	Inter-comment gaps	Sort by created_utc, compute deltas	Uniform gaps (e.g. 7min) = automation; random = human
F6	Subreddit rotation order	Sequence of subreddits commented in	Same order each session = bot pattern
F7	Comment length distribution	word_count per comment	All similar length = templated; varied = human
F8	Score distribution	Score per comment per subreddit	Low scores across the board = content not landing
F9	Question-ending rate	% of comments ending with ”?” per subreddit	Question-back pattern rate
F10	Vagueness rate	% of comments flagged as vague (A24)	The BotBouncer-reported pattern
F11	Reply thread depth	Check if any comments have child replies	Fire-and-forget vs genuine conversation
F12	Deleted comment detection	Gaps in comment_id sequence	Double-comments that were deleted

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Section G: Cross-Account Correlation (Needs All 5 Accounts’ Data)

Compute After All Accounts Are Fetched

#	Analysis	How to Compute	Purpose
G1	Subreddit overlap matrix	For each pair of accounts, count shared subreddits	High overlap = coordinated farming
G2	Timing correlation	For each pair, check if comments are within same time window	Same-session activity = coordination
G3	Comment similarity (cross-account)	Pairwise comparison of comment bodies	Same AI prompt → similar comments
G4	Swarm participation overlap	Cross-reference with swarm_campaigns/swarm_actions	Which accounts acted on same posts
G5	IP/proxy sharing matrix	For each pair, check if they shared IP/proxy	IP correlation = account linking
G6	Account creation cohort	Group by creation date	March cohort vs June cohort ban rate
G7	Karma trajectory comparison	Plot karma over time for all 5	Banned vs safe trajectory differences
G8	Comment style fingerprint	Structural analysis: opener pattern, sentence structure, vocabulary	Same prompt = same style fingerprint

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Section H: CQS (Contributor Quality Score)

Fetch Method

For each banned account (if still able to post):
1. Visit r/WhatIsMyCQS
2. Create a new post with the word "test"
3. Bot responds with the account's current CQS tier

NOTE: Banned accounts cannot post. This check should be done on ACTIVE accounts only.
For banned accounts, CQS is unknowable post-ban — but if we have pre-ban CQS data in the DB, use that.

#	Data Point	How to Get	Purpose
H1	Pre-ban CQS (if logged)	Check reddit_metrics.db for CQS field	Was CQS already declining before ban?
H2	Current CQS for active accounts	r/WhatIsMyCQS test post	Check if active accounts are also at risk

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Section I: Browser Fingerprint & Proxy Data (From AdsPower)

From AdsPower Profile API

#	Data Point	Source	Purpose
I1	Canvas fingerprint	AdsPower profile config	Check for fingerprint sharing across accounts
I2	WebGL renderer	AdsPower profile config	Same
I3	Font list	AdsPower profile config	Same
I4	Screen resolution	AdsPower profile config	Same
I5	Timezone	AdsPower profile config	Should match account’s assigned timezone
I6	User agent	AdsPower profile config	Should be consistent per profile
I7	Proxy IP assigned	AdsPower profile config	Match against BAN-PATTERN-HANDOFF IPs
I8	Proxy type	AdsPower profile config	Webshare vs Decodo
I9	Profile creation date	AdsPower API	When was the profile created?
I10	Proxy change history	AdsPower API or logs	Has the proxy ever been changed? (IP change = fingerprint shift)

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Section J: Swarm Campaign Data (If Available)

From reddit_metrics.db

#	Data Point	Table	Purpose
J1	All swarm campaigns	swarm_campaigns	What campaigns were run?
J2	Actions per campaign	swarm_actions	Which accounts did what in each campaign?
J3	Target post per campaign	swarm_campaigns.target_post	What post was targeted?
J4	Action timing	swarm_actions.timestamp	Were actions within a tight time window?
J5	Action type	swarm_actions.action	upvote, comment, etc.
J6	Playbook used	swarm_campaigns.playbook	Which playbook template was used?

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Section K: Account Creation Data (If Available)

#	Data Point	How to Get	Purpose
K1	Creation date	about.json → created_utc	Already in profile-registry
K2	Creation IP	AdsPower profile creation logs	Check for batch creation from same IP
K3	Creation browser fingerprint	AdsPower profile creation logs	Check for shared fingerprints at creation
K4	Email used for registration	AdsPower profile notes or Reddit account settings	Check for email pattern similarity
K5	Username pattern	Visual inspection	”Adjective_Noun_Number” pattern across accounts
K6	Verified email status	about.json → has_verified_email	CQS factor, unverified = lower CQS

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Output Format

Consolidated Data File

{
  "metadata": {
    "collection_date": "2026-08-12",
    "accounts_analyzed": ["hailybarnes37", "joycehicks2026", "Key_Character6482", "Ok_Bobcat9406", "delilahmelendez30"],
    "data_source": "Reddit JSON API via hailybarnes37 proxy + AdsPower API + reddit_metrics.db",
    "transport": "curl via 213.201.251.213:5407 (Webshare AEST)",
    "rate_limit": "7+ second delay between requests"
  },
  "accounts": {
    "hailybarnes37": {
      "profile": { ... Section C ... },
      "comments": [ ... Section A ... ],
      "overview": [ ... Section B ... ],
      "botbouncer": { ... Section D ... },
      "subreddit_bans": [ ... Section E ... ],
      "timing_analysis": { ... Section F ... },
      "fingerprint": { ... Section I ... },
      "swarm_data": { ... Section J ... },
      "creation_data": { ... Section K ... }
    },
    ...
  },
  "cross_account_analysis": { ... Section G ... }
}

Analysis Prompt

A model-agnostic ANALYSIS_PROMPT.md will be generated after data collection, asking the analysis model to:

1. Rank detection vectors by severity for each account
2. Identify the most likely primary trigger for each ban
3. Identify shared patterns across all 5 banned accounts
4. Compare banned vs active accounts on each vector
5. Produce actionable recommendations for preventing future bans

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Fetching Priority

Priority	Section	Why First
P0 (Critical)	Section A — Comment History	Core data for all analysis
P0 (Critical)	Section C — Account Profile (logged-out)	Confirms ban status
P1 (High)	Section E — Subreddit Bans (from DB)	Links bans to specific comments
P1 (High)	Section D5-D6 — BotBouncer source code	Get actual karma-farming sub list
P2 (Medium)	Section B — Overview	Post history context
P2 (Medium)	Section I — Fingerprint data	Check fingerprint sharing
P2 (Medium)	Section J — Swarm data	Check coordination patterns
P3 (Lower)	Section G — Cross-account analysis	Computed after all accounts fetched
P3 (Lower)	Section H — CQS	Active accounts only (banned can’t be checked)
P3 (Lower)	Section K — Creation data	May not be available