Surviving Account Analysis: Reasonable_Owl_3998
Purpose: Control group comparison — analyzing a surviving (not banned) account to determine which behavioral patterns are unique to banned accounts vs. universal across all accounts (both banned and surviving).
Profile: 57 (kpe039j) | Timezone: EDT | Status: Active (not suspended) Account Created: 2026-06-17 (58 days old) Karma: 364 comment, 1 link, 365 total Comments Analyzed: 112 (full API fetch via own cookies + proxy)
Side-by-Side Comparison
| Metric | hailybarnes37 (BANNED) | Key_Character6482 (BANNED) | Reasonable_Owl_3998 (SURVIVING) |
|---|---|---|---|
| Total comments | 172 | 83 | 112 |
| Question-back % | 69.8% | 72.3% | 65.2% |
| Top-level % | 99.4% | 96.4% | 99.1% |
| Edit rate % | 0.6% | 1.2% | 0.0% |
| Median score | 1 | 1 | 1 |
| Avg score | 2.3 | 7.5 | 4.5 |
| Max score | 75 | 454 | 108 |
| Avg word count | 64.6 | 63.8 | 61.8 |
| Karma-farming subs % | 61.0% | 44.6% | 44.6% |
| BotBouncer-monitored subs % | 61.0% | 44.6% | 44.6% |
| Min gap between comments (min) | 2.1 | 2.2 | 2.1 |
| Median gap (min) | 9.6 | 12.7 | 8.4 |
| Max comments in one day | 17 | 14 | 14 |
| Double comments | 6 | 11 | 14 |
| NTA start % | 1.7% | 15.7% | 14.3% |
| Subreddit count | 25 | 13 | 10 |
Key Finding: The Surviving Account Shares MOST Banned-Account Patterns
This is the most important finding from the control group analysis: the surviving account exhibits nearly all the same behavioral patterns as the banned accounts.
Patterns PRESENT in the surviving account (same as banned):
| Pattern | Banned Accounts | Surviving Account | Interpretation |
|---|---|---|---|
| 65%+ question-back rate | 69.8%, 72.3% | 65.2% | All accounts end comments with questions. This is caused by the V1 system prompt instruction “End with a short question if it fits naturally.” The surviving account has a slightly lower rate but still high. |
| 99%+ top-level comments | 99.4%, 96.4% | 99.1% | All accounts almost never reply to other comments. Fire-and-forget pattern is universal. |
| 0% edit rate | 0.6%, 1.2% | 0.0% | No account edits comments. The surviving account is even more extreme. |
| Min gap < 3 min | 2.1, 2.2 | 2.1 | All accounts have rapid-fire comment bursts within the same session. |
| Median score = 1 | 1, 1 | 1 | All accounts have the same score distribution — most comments score 1. |
| Avg word count ~60-65 | 64.6, 63.8 | 61.8 | All accounts produce similar-length comments. Caused by prompt instruction “Keep it short. 2-8 sentences max.” |
| Double comments present | 6, 11 | 14 | The surviving account has MORE double comments than hailybarnes37. This is NOT a discriminator. |
| Max 14+ comments/day | 17, 14 | 14 | All accounts have high-volume days. |
Patterns where the surviving account DIFFERS:
| Metric | Direction | Difference | Interpretation |
|---|---|---|---|
| Subreddit count | SURVIVING has FEWER (10 vs 25, 13) | -47% vs banned avg | The surviving account is active in FEWER subreddits, not more. This contradicts the hypothesis that subreddit diversity protects against bans. |
| Karma-farming subs % | SURVIVING has LOWER (44.6% vs 61%) | -15% vs banned avg | The surviving account uses fewer karma-farming subs. But Key_Character6482 (banned) also had 44.6%, so this is not a discriminator. |
| Max score | SURVIVING has LOWER (108 vs 75, 454) | -59% vs banned avg | The surviving account has not had any viral comments. Banned accounts had higher peak scores. |
| NTA start % | SURVIVING has HIGHER (14.3% vs 1.7%, 15.7%) | +64% vs banned avg | The surviving account starts more comments with “NTA” — but Key_Character6482 (banned) also had 15.7%, so this is not a discriminator. |
| Double comments | SURVIVING has MORE (14 vs 6, 11) | +65% vs banned avg | The surviving account has MORE double comments than hailybarnes37. Double-commenting is NOT a ban predictor. |
Evidence-Based Conclusions
CONCLUSION 1: The universal patterns are NOT ban predictors
Supporting evidence: The surviving account shares 65.2% question-back, 99.1% top-level, 0% edits, 2.1 min min-gap, median score=1, and ~62 avg words — all within 10% of the banned account averages.
Contradicting evidence (for the “these patterns cause bans” hypothesis): If these patterns caused bans, the surviving account should also be banned. It is not. The account has been active for 58 days without suspension.
Assessment: The universal patterns (question-back, top-level dominance, no edits, short comments, rapid gaps) are produced by the SAME RPA task and the SAME system prompt across ALL accounts. They are necessary but not sufficient conditions for detection. They create a detectable fingerprint, but something ELSE triggers the actual ban.
CONCLUSION 2: Double comments are NOT a ban discriminator
Supporting evidence: The surviving account has 14 double comments — MORE than hailybarnes37 (6) and close to Key_Character6482 (11). Yet it is not banned.
Contradicting evidence: None — this finding is straightforward.
Assessment: Double-commenting, previously flagged as a potential issue in the hailybarnes37 analysis, is present in the surviving account at an even higher rate. This eliminates double-commenting as a ban predictor.
CONCLUSION 3: Subreddit diversity does NOT protect against bans
Supporting evidence: The surviving account has only 10 subreddits (fewer than both banned accounts: 25 and 13). If diversity were protective, the surviving account should have MORE subreddits, not fewer.
Contradicting evidence: None directly. One could argue the surviving account hasn’t been active long enough to expand, but it has 58 days of activity.
Assessment: The hypothesis that “commenting across more subreddits appears more human” is not supported. The surviving account is active in FEWER subreddits and is not banned.
CONCLUSION 4: Karma-farming sub concentration is NOT a discriminator
Supporting evidence: The surviving account has 44.6% karma-farming subs — identical to Key_Character6482 (banned). hailybarnes37 (banned) had 61%. The surviving account matches one banned account exactly.
Assessment: Karma-farming sub concentration cannot distinguish banned from surviving accounts.
CONCLUSION 5: The ban trigger is NOT in the behavioral patterns we’ve measured
Supporting evidence: Across 16 metrics, the surviving account is statistically indistinguishable from the banned accounts. The behavioral fingerprint (question-back, top-level, no edits, short comments, rapid gaps, double comments, median score=1) is identical.
Contradicting evidence: None — we could not find a single metric that clearly separates banned from surviving accounts.
Assessment: This is the most important conclusion. The ban trigger must be something we have NOT measured:
- IP-level detection: The surviving account shares an IP with another profile (noted in registry: “Shares IP with Terrible_Risk8486”). If IP-level detection were the trigger, this account should be at risk too — but it’s not banned yet.
- Account creation timing: Banned accounts Upstairs-Fortune-258, OutcomeAdept315, and Ok_Bobcat9406 were all created around Aug 8-9 and banned within days — suggesting batch detection of co-created accounts.
- Reddit’s internal risk scoring: Reddit may assign a risk score based on factors we cannot observe (browser fingerprint consistency, navigation patterns, API call patterns, timing of account creation relative to activity).
- BotBouncer cascades: 2 of 6 banned accounts had BotBouncer bans. The surviving account has 0 BotBouncer bans. BotBouncer may be a necessary gateway for some bans — once flagged by BotBouncer, the account enters Reddit’s watchlist.
- Time: The surviving account may simply not have been caught yet. 58 days is not a long survival period.
What This Means for the Ban Forensics Analysis
The control group analysis invalidates several previously-stated hypotheses:
| Previous Hypothesis | Status After Control Group | Evidence |
|---|---|---|
| ”70% question-back rate is a strong behavioral signal causing bans” | INVALIDATED | Surviving account has 65.2% — near identical. |
| ”Double comments are a ban risk” | INVALIDATED | Surviving account has MORE double comments (14 vs 6). |
| ”Low subreddit diversity makes accounts detectable” | INVALIDATED | Surviving account has FEWER subreddits (10 vs 25, 13). |
| ”Karma-farming sub concentration triggers detection” | INVALIDATED | Surviving account matches banned Key_Character6482 exactly (44.6%). |
| ”Min gap < 4 min is a bot signal” | INVALIDATED | Surviving account has 2.1 min min-gap — same as banned accounts. |
| ”Fire-and-forget (99% top-level) causes bans” | INVALIDATED | Surviving account has 99.1% top-level — same as banned. |
What REMAINS as potential ban triggers:
- BotBouncer as a gateway: 2 of 6 banned accounts had BotBouncer bans. 0 of 1 surviving accounts had BotBouncer bans. This correlation is weak (sample size too small) but directionally consistent.
- Account creation batch detection: 3 banned accounts (Upstairs-Fortune-258, OutcomeAdept315, Ok_Bobcat9406) were created on the same days and banned quickly. The surviving account was created on a different date (Jun 17).
- IP-level factors: The surviving account shares an IP but is not banned — suggesting IP alone is not the trigger, or the co-IP account is also surviving.
- Unmeasured factors: Browser fingerprint consistency, navigation patterns, API request patterns, session duration, or Reddit’s internal risk model.
Limitations
- Sample size: This is a comparison of 1 surviving account vs 6 banned accounts. One surviving account is insufficient to draw statistically significant conclusions.
- Survivorship bias: The surviving account may be banned tomorrow. “Not banned yet” does not mean “will never be banned.”
- Different RPA versions: The banned accounts ran an earlier RPA version. The surviving account may be running a different version. The behavioral patterns may differ if the prompt or flow changed.
- Different timeframes: The banned accounts were active during different periods. Reddit’s detection systems may have been updated between their activity and the surviving account’s activity.
Raw Data
- Comments file:
C:\Users\Administrator\Reasonable_Owl_3998_comments.json(112 comments) - About data:
C:\Users\Administrator\Reasonable_Owl_3998_about.json - Subreddits: r/GirlDinnerDiaries (32), r/AmItheAsshole (26), r/Advice (13), r/movies (11), r/gaming (10), r/NoStupidQuestions (8), r/explainlikeimfive (6), r/CasualConversation (3), r/mildlyinfuriating (2), r/NewToReddit (1)
- Account status: is_suspended=False, has_verified_email=True, verified=True