⁂ George Ho

Understanding Hate Speech on Reddit through Text Clustering

Note: the following article contains several examples of hate speech (including but not limited to racist, misogynistic and homophobic views).

Have you heard of /r/TheRedPill? It’s an online forum (a subreddit, but I’ll explain that later) where people (usually men) espouse an ideology predicated entirely on gender. “Swallowers of the red pill”, as they call themselves, maintain that it is men, not women, who are socially marginalized; that feminism is something between a damaging ideology and a symptom of societal retardation; that the patriarchy should actively assert its dominance over female compatriots.

Despite being shunned by the world (or perhaps, because of it), /r/TheRedPill has grown into a sizable community and evolved its own slang, language and culture. Let me give you an example.

Cluster #14:
Cluster importance: 0.0489376285127
shit: 2.433590
test: 1.069885
frame: 0.396684
pass: 0.204953
bitch: 0.163619

This is a snippet from a text clustering of /r/TheRedPill — you don’t really need to understand the details right now: all you need to know is that each cluster is simply a bunch of words that frequently appear together in Reddit posts and comments. Following each word is a number indicating its importance in the cluster, and on line 2 is the importance of this cluster to the subreddit overall.

As it turns out, this cluster has picked up on a very specific meme on /r/TheRedPill: the concept of the shit test, and how your frame can pass the shit tests that life (but predominantly, bitches) can throw at you.

There’s absolutely no way I could explain this stuff better than the swallowers of the red pill themselves, so I’ll just quote from a post on /r/TheRedPill and a related blog.

The concept of the shit test very broad:

… when somebody “gives you shit” and fucks around with your head to see how you will react, what you are experiencing is typically a (series of) shit test(s).

A shit test is designed to test your temperament, or more colloquially, “determine your frame”.

Frame is a concept which essentially means “composure and self-control”.

… if you can keep composure/seem unfazed and/or assert your boundaries despite a shit test, generally speaking you will be considered to have passed the shit test. If you get upset, offended, doubt yourself or show weakness in any discernible way when shit tested, it will be generally considered that you failed the test.

Finally, not only do shit tests test your frame, but they also serve a specific, critical social function:

When it comes right down to it shit tests are typically women’s way of flirting.

… Those who “pass” show they can handle the woman’s BS and is “on her level”, so to speak. This is where the evolutionary theory comes into play: you’re demonstrating her faux negativity doesn’t phase you [sic] and that you’re an emotionally developed person who isn’t going to melt down at the first sign of trouble. Ergo you’ll be able to protect her when threats to her safety emerge.

If you want to learn more, I took all the above quotes from here and here: feel free to toss yourself down that rabbit hole (but you may want to open those links in Incognito mode).

Clearly though, the cluster did a good job of identifying one topic of discussion on /r/TheRedPill. In fact, not only can clustering pick up on a general topic of conversation, but also on specific memes, motifs and vocabulary associated with it.

Interested? Read on! I’ll explain what I did, and describe some of my other results.

Reddit is — well, it’s pretty hard to describe what Reddit is, mainly because Reddit comprises several thousand communities, called subreddits, which center around topics broad (/r/Sports) and niche (/r/thinkpad), delightful (/r/aww) and unsavory (/r/Incels).

Each subreddit is a unique community with its own rules, culture and standards. Some are welcoming and inclusive, and anyone can post and comment; others, not so much: you must be invited to even read their front page. Some have pliant standards about what is acceptable as a post; others have moderators willing to remove posts and ban users upon any infraction of community guidelines.

Whatever Reddit is though, two things are for certain:

  1. It’s widely used. Very widely used. At the time of writing, it’s the fourth most popular website in the United States and the sixth most popular globally.

  2. Where there is free speech, there is hate speech. Reddit’s hate speech problem is well documented, the center of recent controversy, and even the subject of statistical analysis.

Now, there are many well-known hateful subreddits. The three that I decided to focus on were /r/TheRedPill, /r/The_Donald, and/r/CringeAnarchy.

The goal here is to understand what these subreddits are like, and expose their culture for people to see. To quote Steve Huffman, Reddit’s CEO:

“I believe the best defense against racism and other repugnant views, both on Reddit and in the world, is instead of trying to control what people can and cannot say through rules, is to repudiate these views in a free conversation, and empower our communities to do so on Reddit.”

And there’s no way we can refute and repudiate these deplorable views without knowing what those views are. And instead of spending hours of each of these subreddits ourselves, let’s have a machine learn what gets talked about on these subreddits.

Now, how do we do this? This can be done using clustering, a machine learning technique in which we’re given data points, and tasked with grouping them in some way. A picture will explain better than words:

Illustration of clustering

The clustering algorithm was hard to decide on. After several dead ends were explored, I settled on non-negative matrix factorization of the document-term matrix, featurized using tf-idfs. I don’t really want to go into the technical details now: suffice to say that this technique is known to work well for this application (perhaps I’ll write another piece on this in the future).

Finally, we need our data points: Google BigQuery has all posts and comments across all of Reddit, from the the beginning of Reddit right up until the end of 2017. We decided to focus on the last two months for which there is data: November and December, 2017.

I could talk at length about the technical details, but right now, I want to focus on the results of the clustering. What follows are two hand-picked clusters from each of the three subreddits, visualized as word clouds (you can think of word clouds as visual representations of the code snippet above), as well as an example comment from each of the clusters.


You already know /r/TheRedPill, so let me describe the clusters in more detail: a good number of them are about sex, or about how to approach girls. Comments in these clusters tend to give advice on how to pick up girls, or describe the social/sexual exploits of the commenter.

What is interesting is that, as sex-obsessed as /r/TheRedPill is, many swallowers (of the red pill) profess that sex is not the purpose of the subreddit: the point is to becoming an “alpha male”. Even more interesting, there is more talk about what an alpha male is, and what kind of people aren’t alpha, than there is about how people can become alpha. This is the first cluster shown below, and comprises around 3% of all text on /r/TheRedPill.

The second cluster comprises around 6% of all text on /r/TheRedPill, and contains comments that expound theories on the role of men, women and feminism in today’s society (it isn’t pretty). Personally, the most repugnant views that I’ve read are to be found in this cluster.

I feel like the over dramatization of beta qualities in media/pop
culture is due to the fact that anyone representing these qualities is
already Alpha by default.

The actors who play the white knight lead roles, the rock stars that
sing about pining for some chick... these men/characters are already
very Alpha in both looks and status, so when beta BS comes from their
mouths, it’s seen as attractive because it balances out their already
alpha state into that "mostly alpha but some beta" balance that makes
women swoon.

/r/TheRedPill cluster #13 /r/TheRedPill cluster #6

Since the dawn of humanity men were always in control, held all the
power and women were happy because of it. But now men are forced to
lose their masculinity and power or else they'll be killed/punished by
other pussy men with big guns and laws who believe feminism is the
right path for humanity.


Feminism is really a blessing in disguise because it's a wake up call
for men and a hidden cry for help from women for men to regain their
masculinity, integrity and control over women.



You may have already heard of /r/The_Donald (a.k.a. the “pro-Trump cesspool”), famed for their takeover of the Reddit front page, and their involvement in several recent controversies. It may therefore be surprising to learn that there is an iota of lucid discussion that goes on, although in a jeering, bullying tone.

/r/The_Donald is the subreddit which has developed the most language and inside jokes: from “nimble navigators” to “swamp creatures”, “spezzes” to the “Trumpire”… Explaining these memes would take too long: reach out, or Google, if you really want to know.

The first cluster accounts for 5% of all text on /r/The_Donald, and contains (relatively) coherent arguments both for and against net neutrality. The second cluster accounts for 1% of the all text on /r/The_Donald, and is actually from the subreddit’s MAGABrickBot, which is a bot that keeps count of how many times the word “brick” has been used in comments, by automatically generating this comment.

So much misinformation perpetuated by the Swamp... Abolishing Net
Neutrality would benefit swamp creatures with corporate payouts but
would be most damaging to conservatives long term.

Net Neutrality was NOT created by Obama, it was actually in effect
from the very beginning...
/r/The_Donald cluster #0 /r/The_Donald cluster #2

We are at **14.3173880911%** of our goal to **BUILD THE WALL**
starting from Imperial Beach, CA to Brownsville, Texas! Lets make sure
everyone gets a brick in the United States! For every Centipede a
brick, for every brick a Centipede!

At this rate, the wall will be **1071.35224786 MILES WIDE** and
**353.552300867 FEET HIGH** by tomorrow! **DO YOUR PART!**


On the Internet, cringe is the second-hand embarrassment you feel when someone acts extremely awkwardly or uncomfortably. And on /r/CringeAnarchy you can find memes about the real cringe, which is, um, liberals and anyone else who advocates for an inclusionary, equitable ideology. Their morally grey jokes run the gamut of delicate topics: gender, race, sexuality, nationality…

In some respects, the clustering provided very little insight into this subreddit: each such delicate topic had one or two clusters, and there’s nothing really remarkable about any of them. This speaks to the inherent difficulty of training a topic model on memes: I rant at greater length about this topic on one of my blog posts.

Both clusters below comprise around 3% of text on /r/CringeAnarchy: one is to do with race, and the other is to do with homosexuality.

Has anyone here, non-black or otherwise, ever wished someone felt
sorry for being black? Maybe it's just where I live... the majority is
black. It's whatever.
/r/CringeAnarchy cluster #8 /r/CringeAnarchy cluster #8

Also, the distinction between bisexual and gay is academic. If you do
a gay thing, you have done a gay thing. That's what "being gay" means
to a LOT of people. Redefining it is as useful as all the other things
SJWs are redefining.

As much information as that might have been, this was just a glimpse into what these subreddits are like: I made 20 clusters for each subreddit, and you could argue that (for somewhat technical reasons) 20 clusters isn’t even enough! Moreover, there is just no way I could distill everything I learned about these communities into one Medium story: I’ve curated just the more remarkable or provocative results to put here.

If you still have the stomach for this stuff, scroll through the complete log files here, or look through images of the word clouds here.

Finally, as has been said before, “Talk is cheap. Show me the code.” For everything I’ve written to make these clusters, check out this GitHub repository.

Update (2018-11-08): If you’re interested in the technical, data science side of the project, check out the slide deck and speaker notes from my recent talk on exactly that!

#Machine-Learning #Natural-Language-Processing