Reddit AI-generated videos and other posts: which ones commenters call AI

You've probably seen the argument. Someone posts a clip of a dog doing something a dog shouldn't be able to do, and a reply shows up: "this is AI." Someone else says it's real. On Reddit, real or AI is a familiar fight in the comments. I wanted to know whether video posts on Reddit really draw that comment more than other kinds of posts, or whether it just feels that way.

So I counted. I took 100 large English-language subreddits and nearly every post from the start of 2022 through late September 2026, and kept the 20,682,632 posts that got at least one top-level comment from someone other than the poster, a known bot, and not distinguished as a moderator's, in their first week. Then I asked the data one question. Do video posts get called AI more often than text posts, and by how much?

I didn't try to judge whether any post was actually made by AI. That's a different and much harder question. I only counted what people said, which is the part you actually see when you scroll. A post counts here if one of its top-level comments, from someone other than the poster, used one of nine phrases within a week: things like "this is AI", "AI slop", "written by ChatGPT" or "clearly AI".

How often does each kind of post get called AI?

From January to September 2026, 1.15% of video posts that got at least one top-level comment, in 100 large subreddits, had a comment calling them AI (one of nine phrases), after adjusting for false matches. For text posts in the same 100 subreddits and period it was 0.19%. You'll find link and image posts in the chart below, with their ranges.

Those are adjusted numbers, and the adjustment matters. Not every match is an accusation. Under a link, "AI slop" may be about the topic rather than the post; I did not measure that. So I had samples of matches labelled, and I scaled each format by how often a match really meant the post. Here's how that compares with the raw counts:

The bars for video, link and image posts overlap, so I won't rank those three against each other. Link posts drop the most once you remove the false matches, and I'll show below how many of those matches weren't about the post. What does hold up is video against text, and that's where it gets interesting.

Try itHow often a phrase like "this is AI" shows up in a subreddit you pick: Historical search

Are Reddit video posts called AI more often than text posts?

I counted all video posts, not only the ones that really are AI-made. In 100 large subreddits from January to September 2026, the adjusted share of video posts that got a comment saying AI made them, among posts that got at least one top-level comment, was about 6.0× the text share (range 3.1 to 11.5). Counted other reasonable ways, it lands between 3.6× and 6.8×.

That's a wide range, so I'd read it as "several times," not as one exact number. But I don't think it's an accident. I tried to break it a few ways and it didn't break.

First, I looked inside each subreddit, since a subreddit full of videos might just be a grumpier place. Among 59 of the 100 subreddits with at least 200 video and 200 text posts that got a comment in January to September 2026, the raw share of video posts with a matching comment beat text in 52.

Second, I'd noticed the video pattern in an early look at the same data, before I wrote the plan. That's the kind of thing that can fool you. So I checked 2025, a separate period from my early look, in the same subreddits. From January to September 2025, in the same 100 subreddits, 0.59% of video posts and 0.11% of text posts that got a comment had a comment using one of the nine phrases (raw, not adjusted). It's the same direction.

Third, one subreddit stands out. Among subreddits with lots of video posts, r/interestingasfuck has the highest raw share of them with a matching comment. If you drop it, the gap shrinks but it doesn't go away. Here's the ratio counted several ways:

Every line in that table has video above text. The exact size of the gap depends on choices I had to make, though, so treat the ratio as a ballpark.

Is it the number of comments, not the format?

Partly, but it doesn't close the gap. In this data, 24.1% of video posts and 20.1% of text posts drew ten or more top-level comments in their first week, and every extra comment is one more chance that somebody types "this is AI." So I split posts into groups by how many top-level comments they got in their first week.

If the format didn't matter, video and text would line up inside each group. Here's what they actually do:

When posts are grouped by top-level comments in the first week, the raw video share was 3.7× to 5.1× the text share in every group (100 large subreddits, January to September 2026). The more comments a post gets, the more likely one of them says AI, for both kinds of posts. You'd expect that. What you might not expect is that video stays well ahead at every level.

So when you hear that everyone calls videos AI, part of it is just that videos get talked about more: more comments, more chances for one of the nine phrases. Not all of it, though.

Are commenters right when they say a post is AI?

I can't tell you that. I didn't check whether any post was really made by AI, and commenters can be wrong both ways. What I could check is whether a matching comment really accuses the post, and that depends a lot on the format.

That matters if you're reading any count like this one, including mine. Under a link, "AI slop" may be about the topic rather than the post; I did not measure that. In a labelled sample of 75 matches per format from 2026, about three in four video matches (74.7%) were real accusations, against about one in three link matches (36.0%). You can't treat the two as the same thing.

I had a sample of matches from each format labelled. Here's the share where the comment really said AI made this post:

In a labelled sample of 75 video posts from 2026, 74.7% of phrase matches really said AI made the post (range 63.8% to 83.1%). Link posts had the lowest share, 36.0%, of phrase matches in a labelled sample of 75 link posts from 2026 (range 26.1% to 47.3%). Under link posts, 48 of the 75 sampled matches were not accusations of the post; one possible reason, not measured, is that many are about AI as a topic.

Of the link posts with a matching comment in January to September 2026, 59.3% were in r/technology and 20.0% in r/politics (100 large subreddits). So I don't treat "link" as a post format in this story. 79.2% of the link posts with a matching comment were in those two subreddits, so the link result mostly reflects two communities.

How has the share of posts with a comment using these AI phrases changed?

In 82 subreddits with steady activity, the raw share of video posts that got a comment using one of nine AI phrases rose from 0.03% in Q3 2023 to 2.06% in Q3 2026 (through September 23); this is not a share of AI posts. Text posts rose too, and the chart has their numbers.

These are raw shares of posts with a comment using one of the nine phrases. They aren't shares of AI posts, and they aren't adjusted for false matches. Here they are by quarter:

I wouldn't read this line as a measure of how much accusing goes on. People may simply have started using these exact phrases, and I didn't measure how many accusations the phrases catch in each year. I also start where I do on purpose. Comments from before June 2023 were saved with a different delay, so I don't compare against them.

Still, the direction is hard to miss. All four lines end far above where they start. What I can't tell you is how much of that is people accusing more and how much is people wording it the same way using these exact phrases. It could be some of both; I didn't measure the split. In a smaller check from 2023 and 2024, with 50 posts per format, 54.0% of matches under video posts were real accusations (range 40.4% to 67.0%), and 17 of 50 matches were people asking whether it was AI, so I don't compare it with today's. That check is not a trend estimate.

If you want the bigger picture, I wrote about how "AI slop" spread through Reddit comments and about the em dash and ChatGPT separately.

So if you post video on Reddit and someone writes "this is AI" under it, it only tells you a commenter used those words; it doesn't tell you what they meant or whether your video is AI: I didn't check the posts, and commenters can be wrong.

Corrections: contact me; each fix gets a dated note on this page. And if there's a question about AI on Reddit you'd like me to ask this data next, tell me that too.

What this data can't tell you

This counts what commenters say and not how many posts are actually made by AI. Commenters can be wrong, and I didn't check the posts themselves. The data shows the pattern, but it does not show why commenters call videos AI more often.

These are 100 large English-language subreddits, every fourth of the 400 most active English-language, non-adult subreddits with at least 200,000 subscribers, as of October 2025, so small, adult-only and non-English communities may look different. Only posts with at least one top-level comment from someone other than the poster, a known bot, and not distinguished as a moderator's, in their first week are counted. Posts nobody answered at the top level aren't in here.

The search catches only nine phrases. Accusations in other words, like "fake" or "Sora," weren't checked at all. A rough check of comments with AI-related words found the phrases miss roughly half of the video accusations and about three in four of the text ones in that pool (a rough estimate from 50 comments per format); the method has the exact numbers. So the shares are rough. They're not a clean floor or ceiling.

The check of how often a match is a real accusation used 75 posts per format, which is a small sample. It read one comment per post, chosen at random, and posts with more comments have more matches, so I don't know which way that tilts the ratio. A separate check did not confirm 4 of the 40 verdicts it looked at. So the shares could be somewhat lower still.

29.8% of the raw video matches in January to September 2026 came from r/interestingasfuck; without it the raw video-to-text ratio falls from 5.2× to 3.8×. 79.2% of the link posts with a matching comment were in r/technology and r/politics, so the link result mostly reflects two communities.

How people word an accusation may change over time; I didn't measure that, so a rise may partly be the phrases themselves catching on. Comments from before June 2023 were saved with a different delay, so I don't read those as a trend. I noticed the video pattern in an early look at the same data, so I checked it on 2025, a separate period in the same subreddits, and inside each subreddit.

Deleted or removed comments have no text left, so they can never match, and I didn't measure how often that differs by format. A post's format comes from its link type: a YouTube link counts as a video, and a post on x.com that holds a video counts as a link. I didn't check how often that's wrong.

Method

Data: 41,725,519 posts from January 1, 2022 to September 23, 2026 (that whole day included) in a fixed list of 100 large English-language, non-adult public subreddits, the same list used in my pieces on "AI slop" and the em dash. Pinned and distinguished posts, accounts on KissMyPost's list of known bots, posts from June 12 to 18, 2023, the first week of the Reddit blackout, which began June 12, and posts from half an hour on July 26, 2023, when comments are missing, are left out. Posts removed by moderators are included; comments under them stay in the data. 20,682,632 posts got at least one top-level comment from someone other than the poster or a known bot, and not distinguished as a moderator's, within seven days, 3,824,775 of them in January to September 2026, when 23,679 had a matching comment.

A matching comment is top-level, not written by the poster, not distinguished as a moderator's and not from a known bot, posted within seven days of the post, and it uses one of nine phrases: "AI slop", "written by AI" or "written by ChatGPT", "sounds like" or "reads like" AI or ChatGPT, "ChatGPT wrote", "AI wrote this", "clearly AI" or "obviously AI", "this is AI", and "AI-generated post". Format: video is a Reddit-hosted video, a link to YouTube or Streamable, or any post Reddit flags as an embedded video; image is an image post, Reddit's or Imgur's image host, or a Reddit gallery; text is a self post; link is everything else, such as x.com links and crossposts.

Labelling: both judges were the same AI model run with different instructions, and they labelled 700 comments without knowing which sample a comment came from. Their agreement was a Cohen's kappa of 0.868 on the 699 comments both of them labelled, where 1 is perfect. A third decided the 55 comments they disagreed on. A separate check of 40 final verdicts that said "real accusation", 10 per format, also done by an AI model, not by a person: 36 confirmed. The samples for how often a match is a real accusation (the share of matches that really say AI made the post) were 75 posts per format from 2026 and 50 per format from 2023 and 2024, one random matching comment each. The check for missed accusations used 50 comments per format from 2026 that had AI-related words but none of the nine phrases; the phrases caught roughly 27.5% of text accusations and 46.0% of video ones in that pool.

The adjusted share is the raw share times the share of matches that really accuse the post. Its range is the wider of two methods: multiplying the two separate ranges, and resampling whole subreddits together with the labelling uncertainty, since posts in one subreddit aren't independent. Video: 1.15% (0.65% to 1.92%). Text: 0.19% (0.13% to 0.28%). Widened for six comparisons between formats, the video share stays at or above 0.57% and the text share at or below 0.32%, so they still don't overlap. The ratio of 6.0× has a 95% confidence interval of 3.1 to 11.5 from resampling subreddits.

The subreddit with the highest raw share for video posts, among those with at least a few hundred of them, is r/interestingasfuck, at 10.5% of its 11,404 video posts in January to September 2026. I re-ran the ratio with other definitions: a broader phrase list, without r/interestingasfuck, the median of per-subreddit ratios, the median of per-subreddit shares, galleries counted as links, comments at every level, an adjustment for missed accusations as well, and the shares scaled by the separate check. The ratio ranged from 3.6× to 6.8×, and video stayed above text in every one; the median-of-shares variant gave 3.7×. For some of these definitions the share of real accusations was held fixed, because it wasn't measured for that definition, so they check the direction rather than give new estimates. For the comment-count check, at the text posts' mix of comment counts the raw video share would be 1.25% instead of 1.54%, against 0.30% for text. Per thousand top-level comments there were 1.67 matching comments under video posts and 0.373 under text posts.

Planned before looking at results (written after one early trial look at the same data, as noted above): video posts would have the highest raw share and text the lowest (didn't hold: on raw matches, link posts had 1.70% and video posts 1.54%); the share would grow at least tenfold in every format from 2022 to 2026 (held on paper, but I don't use it, because the year 2022 has very few matches and comments from before June 2023 were saved differently); video would be ahead of text in most subreddits (held); matches under link posts would be real accusations least often (held); and after adjusting, video would come first and text last (did not hold, because the video range overlaps the link and image ranges). The plan said the headline would need the full order in every specification; it did not hold, so I report only video against text. Video, link and image posts aren't ranked against each other. I also planned to say when video's lead appeared; I can't, so I make no claim about it.

Found while analysing: the control for the number of comments was added after the plan, because video posts get more comments. I added the estimate adjusted for missed accusations too. After a review, the ranges were redone by resampling whole subreddits, widened for six comparisons, and checked on the year 2025 and inside each subreddit. The growth chart starts in the third quarter of 2023 and uses only the 82 subreddits with enough posts in every quarter.

Words like higher or lowest, when they compare formats, appear only where the ranges don't overlap.

Conflict of interest: KissMyPost makes Reddit research tools. Funding: none.

Questions people ask (FAQ)

The data

Seven CSV files come with this article: the adjusted share by format, the share of matches that really accuse the post, the raw share by number of comments, and the quarterly raw share for each format in the steady subreddits. Shares in most files are fractions of one rather than percent, with ranges; the comment-count file uses percent. None of the files contain comment text or usernames. License: CC BY 4.0; credit KissMyPost, link to this page.

• CSVAdjusted share by format in 2026Share of video, link, image and text posts with a comment saying AI made the post, adjusted for false matches, with ranges and post counts, January to September 2026.
• CSVReal accusations among matches in 2026Share of labelled phrase matches where the comment really says AI made the post, by format, with ranges.
• CSVBy number of comments in 2026Raw share of video and text posts with a matching comment, by number of top-level comments in the first week, and the ratio.
• CSVQuarterly raw share, video postsShare of video posts in the steady subreddits with a comment using one of the nine phrases, by quarter, with ranges.
• CSVQuarterly raw share, text postsShare of text posts in the steady subreddits with a comment using one of the nine phrases, by quarter, with ranges.
• CSVQuarterly raw share, image postsShare of image posts in the steady subreddits with a comment using one of the nine phrases, by quarter, with ranges.
• CSVQuarterly raw share, link postsShare of link posts in the steady subreddits with a comment using one of the nine phrases, by quarter, with ranges.
• PNGMain chart as an imageAdjusted share of posts called AI, by format, as an image.

Zenodo DOI: https://doi.org/10.5281/zenodo.24141419