The most toxic subreddits, measured by the share of comments a toxicity model flags as rude

Ranking the most toxic subreddits by the toxicity model is not the whole story, since that model partly just ranks swearing. But when you see internet lists of the most toxic subreddits pop up within seconds, how do they get a rudeness score for every comment? The toxicity model is an obvious tool to use: you give it a comment, and it tells you how rude it sounds. Two automated judges also read through a sample of flagged comments, to see what the model was really counting.

For my data, I used 461,459,367 comments in subreddits marked “safe for work,” posted between January and September 2026. I limited myself to comments that had been scored by Detoxify, and excluded known bots. I called a comment “flagged” if it had been judged toxic by Detoxify, meaning it had received a toxicity score of at least 0.5. (In Detoxify’s training data, that’s described as “a rude, disrespectful, or unreasonable comment.”) I thought of the score as measuring the words used in a comment, rather than a judgment on the authors of those comments or the communities they belonged to.

How toxic is Reddit overall?

On workplace-appropriate subreddits, the model rates 9.36% of scored comments rude, about one in eleven, from January through September 2026. (Raising the threshold to 0.9 gives 5.43%).

A typical large subreddit is 8.06%, where “large” means 3,206 subreddits, each with at least 25,160 scored comments over those nine months.

Not every comment was scored. In fact, only about one in five comments was scored; specifically, comments by known authors, between 20 and 1,000 characters long. That means the scoring process only applies to comments under text posts that were sorted into topic clusters. It’s a sizable chunk of Reddit, but not all of it.

Is swearing the same as being toxic?

No, at least not according to the data from January through September of 2026. Of the 3,206 big subreddits that were considered “safe for work” (SFW) during that time, there were 300 randomly selected comments flagged by Detoxify as “rude,” then judged by two automated processes: only about a third (33.3%) of these comments included a personal or group attack, while 44.7% contained just swearing without an attack.

This is the section that reshapes how you should read everything else, so I’ll be careful here. Two automated judges were used to label a sample of comments flagged by the model and a sample of comments that weren’t flagged. No human double-checked their work by eye. There was a separate automated check, but it was blind to the judges’ answers, and it only looked at 180 comments that spanned all four possible combinations of labels: it agreed with the judges on whether there was an attack or not in 166 of those cases; see the method below for more details.

Here are the judges’ findings, which I drew from two samples.

In the random sample, 22.0 percent of comments that were flagged by the model, about a fifth, were neither swearing nor an attack, and that’s actually more surprising than the share of swearing. (I haven’t checked the content of those comments.)

The subreddit labeled toxic by the model’s score is best read as a mix of swearing and attacks, since the score can’t separate them. Down the ranking, the mix changes.

Among the top-ranked subreddits, when judges read comments flagged by the score, they saw attacks in 58.3% of them. Among the 25 lowest-ranked subreddits, judges read 100 flagged comments (about 4 per subreddit) and saw attacks only 8% of the time; the 95% confidence interval for that number ranges from 4% to 15%. About half of the flagged comments there had neither swearing nor an attack.

There’s a reverse problem too: Detoxify misses attacks. In a sample of 150 randomly chosen comments in large subreddits where the comment scored less than 0.5 on Detoxify, judges still identified attacks in about 4% of them. Since nine out of every ten comments go unflagged by the score, those misses add up. In large subreddits, the 0.5 cut-off captures about half of the attacks judges identify, 48.5%. The 95% confidence interval around that number ranges from 33.5% to 75.0%, so it’s just an estimate.

There are also separate model scores for swearing and for insults, and for the most part they rise together across subreddits. At the very top, however, the two diverge.

Only three subreddits appear on both lists. A simulation of two scores this closely tied would typically expect an overlap of around 13. The swearing list tilts toward fan subreddits devoted to shows, sports and hip-hop. The insult list is mostly devoted to political news.

What is the most toxic subreddit?

The model’s count of the most toxic subreddit, from January through September 2026, was r/TheWordFuck. The machine learning system, called Detoxify, flagged 97.7 percent of its 34,888 scored comments as rude, higher than any other of the 3,206 large safe-for-work subreddits.

In second place is r/Chiraqology, where topic labels say “Music” but the rude share is 30.8 percent. Judges found attacks in only five of 22 flagged comments there, so it’s mostly just swearing. Such rankings might say more about how people write than how they treat each other.

In third place is r/stpaul, which has a rude share of 27.2 percent and was propelled there by a surge in comments earlier this year. The rest of the entries are spread between 25.7 percent and 22.4 percent, after which the list flattens out. The intervals for all neighbouring pairs of subreddits (except one) overlap, so their ranking here doesn’t mean much.

Of the 24 listed, 16 fall under the News & Politics category.

Try itThe comment tone of a subreddit you pick, next to similar subreddits: Subreddits

Which topics on Reddit are the most toxic?

News & Politics is far ahead in terms of toxicity, at least according to Detoxify’s flagging of comments as rude, with the median subreddit being 16.1% of comments flagged. That’s almost twice the rate of Sports, the next topic, which was 8.77% during January through September 2026. Home & Garden and Fashion & Beauty were the lowest rated, at 2.42% and 2.70% respectively. Their relative order isn’t worth much though.

Median per topic across 28 topics, only including subreddits that were scored every month and had a narrow enough confidence interval.

You can see that the topics just under News & Politics tend to cluster together. Sports, Q&As & Stories, Places & Travel, and Pop Culture are all usually around 8% to 9%, and their intervals overlap each other, so there’s no reliable ordering among them.

In contrast, when looking at all 28 topics at once, I widened the intervals to accommodate this. Notice that News & Politics is still clearly separated from the rest.

This probably won’t be a big surprise to people who spend time in political subreddits, but it’s worth pointing out that this is just where the flagged comments were located, not why they were flagged. It’s possible that a single topic could encompass quite different kinds of subreddits. The cause of the gap remains to be measured.

Try itSubreddits on a topic you pick, with who writes in them: Find Subs

What are the least toxic subreddits, and are they the most wholesome subreddits?

The low score isn’t necessarily evidence that these are the most wholesome subreddits. For example, r/kraw has the lowest score among large subreddits (0.11% of comments flagged as rude from January through September 2026), but that doesn’t mean it’s the most wholesome subreddit. Only a tiny fraction of its comments were even scored. Many of the 25 lowest seem like utility communities, with templated comments, tarot readings, giveaways, commissioned art, or daily puzzles. Three of them are tagged as non-English, so it’s also possible that an English-trained model might judge their content differently.

A low share here just means the model saw very few rude words; it’s not saying anything about what else it might have seen in those communities. Since this list can’t find kind communities, because kindness isn’t measured, here are the 25:

r/kraw comes in first, but keep in mind that only a small share of comments were scored, so take this with a grain of salt.

Are bigger subreddits more toxic?

Yes, there is some correlation between subreddit size and toxicity, at least from January through September 2026. I was able to score 16,392 subreddits every month, within a narrow enough interval to make this comparison meaningful, and split them into five subscriber groups. The typical share of comments flagged in the smallest group was 3.75%, and 6.89% in the biggest group, an increase at every step.

I also looked within each topic. In 27 of 28 topics, the share rose with size, and in 23 of 28 it was clear of zero. So there’s still correlation. But that doesn’t mean there’s any prediction that a growing subreddit gets ruder comments, or that there’s any causation from size.

If anything, the overall share is slightly lower for subreddits that grew faster last year. I added a size split to this after seeing the overall correlation. Again, the sign flips within groups of roughly similar-sized subreddits, and there’s no stable relationship with growth.

Do toxic subreddits stay toxic?

I also sorted subreddits by their share of rude comments (according to Detoxify) in the first four months of 2026, and then tracked them for the next five months; these are the 25 subreddits with the highest rank in the earlier period. 18 of them remained in the top 25, out of 3,206 large subreddits, so mostly yes.

All of these are large subreddits, and their order was only slightly different between the two stretches; the rank correlation is 0.969. So a high-listed subreddit was usually high for the whole year.

What was the monthly movement of the share?

The share slid from 11.0% in January to 9.72% in August, then bounced back to 10.2% in September. That’s a spread of 1.3 points; I don’t know why it moved around like that.

So what does a list of toxic subreddits tell you?

One thing it tells you is that this particular toxicity model’s ranking combines two different kinds of things: swearing and attacks, and while attacks are certainly present among the comments that were flagged, they’re only about a third of the problem in big subreddits. Another thing is that 16 of the 24 top-ranked subreddits are in the News & Politics category. So there’s some real information here, but it’s not exactly a list of the cruelest communities on Reddit.

The first two spots on the list are mostly swearing, but the rest of the list is a mix of the two kinds of toxic speech.

Judging a subreddit based solely on its label is inadequate; to make an informed judgment, you’ll have to sample a few threads yourself.

There are also related analyses of whether subreddits are more Democratic or Republican, and how many subreddits there are.

Corrections: contact me; each fix gets a dated note on this page.

Have an idea for what kind of question about the tone of Reddit could be answered with data? Let me know.

What this data can't tell you

Method

Planned before looking, and found while analysing

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

Questions people ask (FAQ)

The data

• CSVHighest-ranked subredditsThe 24 highest-ranked subreddits by share of comments flagged as rude, with 95% intervals, swearing and insult shares, coverage, removed comments and attacks in 22 comments read.
• CSVLowest-ranked subredditsThe 25 subreddits with the lowest flagged share, with 95% intervals, coverage and a low-coverage flag.
• CSVTopicsMedian and pooled flagged share per topic, with bootstrap 95% intervals and the number of subreddits.
• CSVSubscriber groupsMedian flagged share in five equal groups of subreddits by subscribers, with 95% intervals.
• CSVBy month, large subredditsFlagged share per month in the same 3,206 large subreddits, with comment counts and 95% intervals.
• CSVBy month, all SFW subredditsFlagged share per month in all safe-for-work subreddits, with comment counts and 95% intervals.
• CSVJanuary to April checkThe 25 highest-ranked subreddits of January to April and their share in May to September.
• CSVWhat the judges read, by sampleCounts of attack with swearing, attack, swearing only and neither in each of seven samples of comments.
• CSVWhat the judges read, by subredditThe same four labels for 22 flagged comments from each of the 24 highest-ranked subreddits.
• PNGMain chart, 1600 × 1000What comments a toxicity model flags as rude look like when read, as an image.

Zenodo DOI: https://doi.org/10.5281/zenodo.24142919