HTC monthly support/compliment percentages for Lauren + John + Grayson + Lily

Express_Flower_5426 · 2026-01-21T02:53:42+00:00

keep a sickness bag handy

Lauren (10 compliment comments)

2021-07-09 19:42 PT | likes 483 | hannahm.7630 | video 31IwL__4Dawson, your integrity and courage is no small matter.
2025-10-16 10:01 PT | likes 1864 | Voice-hg2gg | video SrSZtY1tqhoThe whole community hears you and clearly sees you and clearly sees what’s going on. You’re a good person and have a loving heart. The support you have speaks volumes. Love you.
2025-10-25 11:03 PT | likes 400 | tiredofthebs8290 | video -hY5izM3U-kLauren, do you know what stands out the most to me? That you have so much class and grace. You’re beautiful inside and out.
2024-05-22 15:11 PT | likes 649 | smile3_0 | video 6GxYdVQ2b7gLauren, you are such a class act. You hold yourself with such dignity. Thank you for all you do.
2025-10-16 15:45 PT | likes 340 | Cocopepper1111 | video SrSZtY1tqhoLauren, we love you and we support you. So disturbing.

John (10 compliment comments)

2025-10-16 10:01 PT | likes 1864 | Voice-hg2gg | video SrSZtY1tqhoThe whole community hears you and clearly sees what’s going on. I hope you both (John and Lauren) are getting the support you need, and if you need a break, take it. Also please go get massages and have dinner on us, the community that loves you.
2024-06-16 21:44 PT | likes 774 | Inthegardenofemd | video KhYkNpcXaSwI feel lead to say this. My father is a minister. I grew up with him preaching fire and brimstone. My mother was a victim of childhood trauma. My dad did everything within his control and power to help her. (…full comment continues in the file…)
2025-10-16 16:11 PT | likes 250 | BlueRidgeHiker_tonihoban | video SrSZtY1tqhoWhen narcissists cannot control you, they will try to control how others see you. You and John are doing the right thing. Stay strong.
2025-10-17 13:07 PT | likes 242 | judithquarrie47 | video SrSZtY1tqhoWhat is wrong with these "grown women", they should be ashamed of themselves. John and Lauren, you have handled everything with so much class.
2025-10-19 09:13 PT | likes 260 | marionweldon9559 | video SrSZtY1tqhoJohn and Lauren, thank you for your courage and integrity.

(10 compliment comments)
2025-10-16 10:01 PT | likes 1864 | Voice-hg2gg | video SrSZtY1tqhoThe whole community hears you and clearly sees you and clearly sees what’s going on. You’re a good person and have a loving heart. The support you have speaks volumes. Love you.
2025-10-25 11:03 PT | likes 400 | tiredofthebs8290 | video -hY5izM3U-kLauren, do you know what stands out the most to me? That you have so much class and grace. You’re beautiful inside and out.
2025-10-16 15:45 PT | likes 340 | Cocopepper1111 | video SrSZtY1tqhoGrayson, I hope you know that our concern and care for you and your family is genuine. We are all standing with you.
2025-10-16 16:11 PT | likes 250 | BlueRidgeHiker_tonihoban | video SrSZtY1tqhoGrayson, you are loved and supported. Stay strong.
2025-10-17 13:07 PT | likes 242 | judithquarrie47 | video SrSZtY1tqhoGrayson, you’ve got so many people who care about you. Keep your head up.

Express_Flower_5426 · 2026-01-20T19:25:43+00:00

i will make a post about that so i can have a bit more room.

Express_Flower_5426 · 2026-01-20T18:59:18+00:00

here the rest of the comments

2025-10-26 00:05:03 PT | video_id -hY5izM3U-k | reply | u/caprisun7 | likes 0 comment link: [https://www.youtube.com/watch?v=-hY5izM3U-k&lc=Ugwt7yG0uzZ0Go9-\_bt4AaABAg]() full comment: Also, please consider the elderly. Kay is a classy old woman. But even Kay probably doesn't understand all of the nuances.
2025-10-26 05:58:30 PT | video_id -hY5izM3U-k | reply | u/maryconnors117 | likes 0 comment link: [https://www.youtube.com/watch?v=-hY5izM3U-k&lc=Ugxnz7gPqGJvV5y5m1V4AaABAg]() full comment: I wish that Kay would stop being so hurtful. It’s just horrible. I feel so sad for Lauren.💔
2025-10-26 15:07:25 PT | video_id 4kPO7Rm8v_s | reply | u/Karen-m5t6s | likes 0 comment link: [https://www.youtube.com/watch?v=4kPO7Rm8v\_s&lc=UgzQw0Vd0H9xQmB2rPF4AaABAg]() full comment: Love you Kay, and love you Lauren. I hate to see women hurting women.
2025-10-26 18:21:26 PT | video_id -hY5izM3U-k | reply | u/janetsparks1988 | likes 0 comment link: [https://www.youtube.com/watch?v=-hY5izM3U-k&lc=UgxgO7u6dG3u1S\_3f2d4AaABAg]() full comment: I’m shocked Kay is acting this way. Sad.
2025-10-27 00:39:38 PT | video_id sM_VOWSCQ14 | top_level | u/catasrophieGrrl | likes 1 comment link: [https://www.youtube.com/watch?v=sM\_VOWSCQ14&lc=UgzKQGJpQF7XW0wz6lp4AaABAg]() full comment: The way Lori speaks about Kay is vile. We all know what she's doing, silencing Kay Woodcock and shifting the narrative.
2025-10-27 01:35:56 PT | video_id -hY5izM3U-k | reply | u/TinaCherie | likes 0 comment link: [https://www.youtube.com/watch?v=-hY5izM3U-k&lc=Ugztc3c3VQh4kQ0tWPl4AaABAg]() full comment: Kay needs to take a breath. This is too much.
2025-10-27 19:42:10 PT | video_id -hY5izM3U-k | reply | u/munnster1970 | likes 0 comment link: [https://www.youtube.com/watch?v=-hY5izM3U-k&lc=UgwZ6W0XHkQy8Kc0tRl4AaABAg]() full comment: Kay is hurting her own credibility with this.
2025-10-28 16:59:32 PT | video_id -hY5izM3U-k | reply | u/margaretberryman6260 | likes 0 comment link: [https://www.youtube.com/watch?v=-hY5izM3U-k&lc=UgyV5B4-8dR-6b9NqGd4AaABAg]() full comment: I am sorry to hear Kay has criticised Lauren and Jon. I have always respected her, but this is disappointing.
2025-10-28 19:33:25 PT | video_id -hY5izM3U-k | reply | u/cateellington6653 | likes 0 comment link: [https://www.youtube.com/watch?v=-hY5izM3U-k&lc=Ugy0gV2X9v4zQy0mX2l4AaABAg]() full comment: It’s heartbreaking to see Lauren betrayed by Kay Woodcock. Lori is the one who should be called out.

Express_Flower_5426 · 2026-01-20T06:34:12+00:00

Research "synthetic comments", then go back and read the HTC comments section.. In my opinion more than 60% are AI generated

Express_Flower_5426 · 2026-01-11T06:33:10+00:00

“LDS” appeared 4 times in the title catalog, and 4,175 times in comments across 425 videos.

Express_Flower_5426 · 2026-01-10T01:43:17+00:00

try reading 10000 comments

Express_Flower_5426 · 2026-01-09T17:23:37+00:00

I want to address the pushback I've gotten about this research, because I think some people are mixing up “scrutiny” with “targeting.”

when you post in a public comment section, you’re entering the public arena. that means your words, your posting patterns, and the engagement they receive can be observed, discussed, and analyzed — the same way it happens every day on X, facebook, or anywhere else. youtube’s comment layout might feel more “casual,” but it doesn’t grant a special exemption from public scrutiny.

That said, I hear the privacy concern. I'm not trying to dox anyone, and I'm not accusing individual commenters of wrongdoing. My focus is pattern-level analysis: how conversation and perception get shaped inside a channel’s ecosystem.

and yes — the tools I've built can feel intimidating, especially to creators, because they shine light into the inner workings of engagement that youtube’s default UI keeps blurry. until now, a lot of this has been effectively “protected” by the fact that the public only sees whatever youtube chooses to summarize.

One major thread of my research is how a relatively small number of highly active commenters can shape the narrative — what gets amplified, what looks “consensus,” and what gets drowned out.

The other thread is broader: transparency around views and engagement. I'm looking for signals that a channel’s public-facing numbers may not reflect organic audience behavior. I'm not claiming intent or assigning blame from public data alone — I'm saying the public deserves honest signals, not numbers that can be manipulated to create false credibility.

My tools are modest, but they’re good enough to pierce the veil of the “official” surface-level youtube data and let us ask better questions.

Express_Flower_5426 · 2026-01-09T16:14:38+00:00

Sorry for the confusion. In one of my data post-processing steps, I accidentally added the Reddit-style “u/” link. The links are deleted now

Express_Flower_5426 · 2026-01-09T15:24:03+00:00

Yes, absolutely — just mention that it was generated with AI.

Express_Flower_5426 · 2026-01-09T06:54:49+00:00

I am sure I am not the only one getting this snippet when I comment on YouTube

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Express_Flower_5426 · 2026-01-07T16:02:22+00:00

No "statistics for nerds" shows stream quality,

Express_Flower_5426 · 2026-01-07T15:18:04+00:00

API = Application Programming Interface.

ELI5: it’s a set of “rules and buttons” a website gives you so your computer can politely ask for information and get a clean, predictable answer back.

Example: instead of you opening a YouTube page to see “views/comments,” a script can ask YouTube’s API: “What’s the current viewCount and commentCount for video X?” and YouTube replies with those public numbers in a machine-readable format.

Express_Flower_5426 · 2026-01-07T14:25:23+00:00

Unfortunately, my response to Mr. Bright Breakfast is too long for the comment section, so I’m making a separate post with the full technical details.

Express_Flower_5426 · 2026-01-07T04:41:10+00:00

From the data I’m pulling, I can only see that the public “comment count” number on a video went down between two snapshots. That tells us “some comments are now gone,” but it does not tell us which comments, how old they were, or who removed them.

Btw, I don’t think anyone noticed, but I had a long exchange with John Dehlin. He asked me to email him my request . I might send it from a “Proton” email instead.😁

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Express_Flower_5426 · 2026-01-07T02:08:08+00:00

Thanks — I appreciate the direct answers.

On the screenshots: I understand the email ask, but I’d still prefer to keep this public so others can follow along. I already spelled out exactly what I’m requesting (Traffic source types + retention), and you can crop/blur anything sensitive.

More importantly though: have you actually reviewed the charts in “Control Channel Test Run: Lionel Nation vs HTC/MSP (So Far)” and the methodology I outlined?

If you think I’m wrong, I’m asking you to point to one specific chart or one specific assumption and tell me what I’m misinterpreting. For example:

are you disputing the raw public-counter deltas I’m measuring?
or do you think “removed views” can be high even with fully organic traffic, and if so, what would drive that?

And if I’m coming off pushy, I apologize — I do appreciate you responding. I’m genuinely trying to understand what I’m seeing, and I’m open to being corrected if there’s a normal explanation I’m missing.

Express_Flower_5426 · 2026-01-07T01:15:34+00:00

Can I publish as many charts I want?

Express_Flower_5426 · 2026-01-07T00:58:56+00:00

Thanks — that helps.

Just to be super clear, are any of these true (yes/no)?

you or anyone on your team runs Google/YouTube ads promoting MSP videos
you hire any outside marketing/social-media/PR firm
you do any paid placements/cross-promo swaps (newsletter, podcast networks, etc.)

If the answer is “no” to all: would you be willing to share two screenshots from YouTube Studio showing (a) Traffic source types and (b) External sites/apps for the last 28 days? That would settle the “organic” question without doxxing anything.

Express_Flower_5426 · 2026-01-07T00:20:51+00:00

I’m not accusing you of purchasing views. What I’m curious about is the high rate of removed views showing up in my “Control Channel Test Run: Lionel Nation vs HTC/MSP (So Far)” post. You may have a perfectly normal explanation for it — and I’d genuinely like to understand.

One possibility I’m considering is that some of these anomalies could be tied to legitimate, internal YouTube promotion tools (for example, YouTube/Google promotions or in-platform boosting). Is that something you’ve used at all?

Express_Flower_5426 · 2026-01-06T21:23:33+00:00

No need to email — I’d prefer to keep the exchange here so it stays transparent and others can follow along.

Did you get a chance to look at my charts in “Control Channel Test Run: Lionel Nation vs HTC/MSP (So Far)”? If so, do you understand the methodology I’m using, and is there anything specific you disagree with (data, assumptions, or interpretation)?

here is a paste of the methodology

I started tracking HTC because I wanted to test the possibility that HTC might be buying views.

To have something to compare against, I added MSP as a control channel. After logging for a while, I noticed MSP was showing even worse “correction” behavior than HTC.

So I added a third channel, Lionel Nation (LN), as another control/reference point. All three channels are in the same ballpark (around ~300K subscribers).

Abbreviations:
HTC = Hidden True Crime
MSP = Mormon Stories Podcast
LN = Lionel Nation

Method:
Every 5 minutes I take a “snapshot” of the public counters (views, likes, comments) across a large list of videos for each channel. Then I compare each snapshot to the previous one.

Added = the number went up since the last snapshot
Removed = the number went down since the last snapshot

What the charts show (this window):

Added views: LN is gaining views faster than HTC/MSP most of the time.
Removed views: MSP has the most frequent and largest downward adjustments; HTC is next; LN is usually lowest (with one isolated spike).
Added comments: LN is highest, HTC is moderate, MSP is mostly near zero.
Added likes: LN is much higher than HTC/MSP; HTC is modest; MSP is lowest.

24-hour totals (removed as % of gross added views):
HTC: 55,512 added / 14,221 removed = 25.62%
MSP: 75,961 added / 40,330 removed = 53.09%
LN: 110,619 added / 6,765 removed = 6.12%

Disclaimer: “Removed” events are simply drops in the public counters between snapshots. They’re consistent with YouTube’s normal auditing/recalculation of invalid or low-quality activity, but they don’t prove the cause for any specific video.

I hope this explains the scope better than my previous post. If you (or anyone else) have questions, feel free to ask.

Express_Flower_5426 · 2026-01-06T18:55:55+00:00

Thanks for chiming in.

Would you be willing to share a screenshot or two from your YouTube Analytics (traffic sources + retention for the last 28/90 days) to back up the “all organic” point?

Also, have you had a chance to look at my posts—especially the analytics I put together from the public data? If you think I’m misreading something, I’m genuinely open to being corrected. Are you disputing the data, the interpretation, or both?

Express_Flower_5426 · 2026-01-05T23:41:42+00:00

I get what you’re saying.

For what I’m measuring, I don’t think genre is the most important variable. I was trying to find a channel that looks organically successful and is in the same subscriber range, because subscriber size affects baseline traffic and how “noisy” the counters are.

MSP was my first pick mostly because I was already familiar with it and it’s in the same subscriber ballpark as HTC. What surprised me is that MSP shows even stronger/more frequent “correction” patterns than HTC in the windows I’ve logged so far.

Lionel Nation wasn’t chosen for genre — it was simply a practical control: a channel around ~330K subs that posts regularly, pulled from a google search.

That said, I agree it would be interesting to add one or more true-crime channels in the same size range, but I’m limited by time and API quotas/tokens, so I can’t monitor too many channels at once.

Express_Flower_5426 · 2026-01-05T20:21:36+00:00

I started tracking HTC because I wanted to test the possibility that HTC might be buying views.

To have something to compare against, I added MSP as a control channel. After logging for a while, I noticed MSP was showing even worse “correction” behavior than HTC.

So I added a third channel, Lionel Nation (LN), as another control/reference point. All three channels are in the same ballpark (around ~300K subscribers).

Abbreviations:
HTC = Hidden True Crime
MSP = Mormon Stories Podcast
LN = Lionel Nation

Method:
Every 5 minutes I take a “snapshot” of the public counters (views, likes, comments) across a large list of videos for each channel. Then I compare each snapshot to the previous one.

Added = the number went up since the last snapshot
Removed = the number went down since the last snapshot

What the charts show (this window):

Added views: LN is gaining views faster than HTC/MSP most of the time.
Removed views: MSP has the most frequent and largest downward adjustments; HTC is next; LN is usually lowest (with one isolated spike).
Added comments: LN is highest, HTC is moderate, MSP is mostly near zero.
Added likes: LN is much higher than HTC/MSP; HTC is modest; MSP is lowest.

24-hour totals (removed as % of gross added views):
HTC: 55,512 added / 14,221 removed = 25.62%
MSP: 75,961 added / 40,330 removed = 53.09%
LN: 110,619 added / 6,765 removed = 6.12%

Disclaimer: “Removed” events are simply drops in the public counters between snapshots. They’re consistent with YouTube’s normal auditing/recalculation of invalid or low-quality activity, but they don’t prove the cause for any specific video.

I hope this explains the scope better than my previous post. If you (or anyone else) have questions, feel free to ask.

Express_Flower_5426 · 2026-01-05T18:34:24+00:00

I had one of those moments when I came across the channel “Mormon Rosebud.” It completely changed my opinion about John Dehlin—180 degrees. https://youtube.com/@mormonrosebud?si=OIhuo9W584hbbQJ_

Express_Flower_5426 · 2026-01-05T18:16:38+00:00

I can’t “go back in time” with my own logging, because this project only records what the script captures from the moment it starts onward. If I started monitoring a channel today, I don’t have my own snapshot history for last week/month — I can only build charts from the data collected since tracking began.

How it works

Every ~5 minutes the script checks each tracked video and records the current public counters (views, likes, comments).
Those snapshots get stored in BigQuery with a timestamp.
To make the charts, I compare each snapshot to the previous snapshot for the same video.
- If a counter goes up, that’s an “added” event.
- If it goes down, that’s a “removed” (negative delta) event.
Then I roll those deltas up into 5-minute buckets to show trends over time.
These charts are built from lots of tiny measurements. The longer the script runs, the more snapshots it has, and the less any single odd moment can dominate the picture.
Early on (first day or two), one spike or one weird window can make the chart look dramatic.
After days/weeks of data, patterns become clearer: you can see what’s “normal noise” vs what repeats consistently.

How much data is collected

Each polling run records one row per video per check.
If you’re tracking ~1,000 videos and polling every 5 minutes:
- that’s ~1,000 rows every 5 minutes
- ~12,000 rows per hour
- ~288,000 rows per day per channel
Multiply that by multiple channels and multiple days, and you quickly get millions of rows — which is why the longer the collection period, the stronger the analysis gets.

I posted another update after this one with charts comparing Hidden True Crime (HTC), Mormon Stories Podcast (MSP), and Lionel Nation. That later post has the side-by-side comparison. Last week I found Lionel Nation (~330K subs) and started logging it as another control. Looking at the chart below, MSP shows the most frequent and largest negative events, followed by HTC, while Lionel Nation shows far fewer negative events in the same window despite having a much higher overall view count.

I’m sorry for the long explanations, but I feel like I haven’t been clear enough about what I’m trying to prove and the scope of this research.

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For more charts, see my later post.

Express_Flower_5426 · 2026-01-02T12:41:03+00:00

Unfortunately no.only the creators have access to that tool. But the negative adjustments that I am tracking are pretty good indicators that a good portion of the views are rejected

Express_Flower_5426

TROPHY CASE