Who in the rainbow can draw the line where the violet tint ends and the orange tint begins? Distinctly we see the difference of the colors, but where exactly does the one first blendingly enter into the other? So with sanity and insanity.
—Herman Melville, Billy Budd
Orange, red? I don’t know what to believe anymore!
—Anonymous, Color Survey
I WILL EAT YOUR HEART WITH A FUCKING SPOON IF YOU AKS ANY MORE QUESTIONS ABOUT COLORS
—Anonymous, Color Survey
Thank you so much for all the help on the color survey. Over five million colors were named across 222,500 user sessions. If you never got around to taking it, it’s too late to contribute any data, but if you want you can see how it worked and take it for fun here.
First, a few basic discoveries:
- If you ask people to name colors long enough, they go totally crazy.
- “Puke” and “vomit” are totally real colors.
- Colorblind people are more likely than non-colorblind people to type “fuck this” (or some variant) and quit in frustration.
- Indigo was totally just added to the rainbow so it would have 7 colors and make that “ROY G. BIV” acronym work, just like you always suspected. It should really be ROY GBP, with maybe a C or T thrown in there between G and B depending on how the spectrum was converted to RGB.
- A couple dozen people embedded SQL ‘drop table’ statements in the color names. Nice try, kids.
- Nobody can spell “fuchsia”.
Overall, the results were really cool and a lot of fun to analyze. There are some basic limitations of this survey, which are discussed toward the bottom of this post. But the sheer amount of data here is cool.
Sex
By a strange coincidence, the same night I first made the color survey public, the webcomic Doghouse Diaries put up this comic (which I altered slightly to fit in this blog, click for original):
It was funny, but I realized I could test whether it was accurate (as far as chromosomal sex goes, anyway, which we asked about because it’s tied to colorblindness) [Note: For more on this distinction, see my follow-up post]. After the survey closed, I generated a version of the Doghouse Diaries comic with actual data, using the most frequent color name for the handful of colors in the survey closest to the ones in the comic:
Basically, women were slightly more liberal with the modifiers, but otherwise they generally agreed (and some of the differences may be sampling noise). The results were similar across the survey—men and women tended on average to call colors the same names.
So I was feeling pretty good about equality. Then I decided to calculate the ‘most masculine’ and ‘most feminine’ colors. I was looking for the color names most disproportionately popular among each group; that is, the names that the most women came up with compared to the fewest men (or vice versa).
Here are the color names most disproportionately popular among women:
- Dusty Teal
- Blush Pink
- Dusty Lavender
- Butter Yellow
- Dusky Rose
Okay, pretty flowery, certainly. Kind of an incense-bomb-set-off-in-a-Bed-Bath-&-Beyond vibe. Well, let’s take a look at the other list.
Here are the color names most disproportionately popular among men:
- Penis
- Gay
- WTF
- Dunno
- Baige
I … that’s not my typo in #5—the only actual color in the list really is a misspelling of “beige”. And keep in mind, this is based on the number of unique people who answered the color, not the number of times they typed it. This isn’t just the effect of a couple spammers. In fact, this is after the spamfilter.
I weep for my gender. But, on to:
RGB Values
Here are RGB values for the first 48 out of about a thousand colors whose RGB values (across the average monitor, shown on a white background) I was able to pin down with a fairly high degree of precision:
The full table of 954 colors is here, also available as a text file here (I have no opinion about whether it should be used to build a new X11 rgb.txt except that seems like the transition would be a huge headache.)
The RGB value for a name is based on the location in the RGB color space where there was the highest frequency of responses choosing that name. This was tricky to calculate. I tried simple geometric means (conceptually flawed), a brute force survey of all potential center points (too slow), and fitting kernel density functions (math is hard). In the end, I used the average of a bunch of runs of a stochastic hillclimbing algorithm. For mostly boring notes on my data handling for this list, see the comments at the bottom of the xkcd.com/color/rgb/ page.
Spelling and Spam
Spelling was an issue for a lot of users:
Now, you may notice that the correct spelling is missing. This is because I can’t spell it either, and when running the analysis, used Google’s suggestion feature as a spellchecker:
A friend pointed out that to spell it right, you can think of it as “fuck-sia” (“fuch-sia”).
Misspellings aside, a lot of people spammed the database, but there were some decent filters in place. I dropped out people who gave too many answers which weren’t colors used by many other people. I also looked at the variation in hue; if people gave the same answer repeatedly for colors of wildly varying hue, I threw out all their results. This mainly caught people who typed the same thing over and over. Some were obviously using scripts; based on the filter’s certainty, the #1 spammer in the database was someone who named 2,400 colors—all with the same racial slur.
Map
Here’s a map of color boundaries for a particular part of the RGB cube. The data here comes from a portion of the survey (1.5 million results) which sampled only this region and showed the colors against both black and white backgrounds.
The data for this chart is here (3.6 MB text file with each RGB triplet named). Despite some requests, I’m not planning to make a poster of any of this, since it seems wrong to take advantage of all this volunteer effort for a profit; I just wanted to see what the results looked like. You’re welcome to print one up yourself (huge copy here), but keep in mind that print color spaces are different from monitor ones.
Basic Issues
Of course, there are basic issues with this color survey. People are primed by the colors they saw previously, which adds overall noise and some biases to the data (although it all seemed to even out in the end). Moreover, monitors vary; RGB is not an absolute color space. Fortunately, what I’m really interested in is what colors will look like on a typical monitors, so most of this data is across the sample of all non-colorblind users on all types of monitors (>90% LCD, roughly 6% CRT).
Color is a really fascinating topic, especially since we’re taught so many different and often contradictory ideas about rainbows, different primary colors, and frequencies of light. If you want to understand it better, you might try the neat introduction in Chapter 35 ofThe Feynman Lectures on Physics (Vol. 1), read Charles Poynton’s Color FAQ, or just peruse links from the Wikipedia article on color. For the purposes of this survey, we’re working inside the RGB space of the average monitor, so this data is useful for picking and naming screen colors. And really, if you’re reading this blog, odds are you probably—like me—spend more time looking at a monitor than at the outdoors anyway.
Miscellaneous
Lastly, here are some assorted things people came up with while labeling colors:
Thank you so much to relsqui for writing the survey frontend, and to everyone else who sacrificed their eyeballs for this project. If you have ideas and want to analyze these results further, I’ve posted the raw data as an SQLite dump here (84 MB .tar.gz file). It’s been anonymized, with IPs, URLs, and emails removed. I also have GeoIP information; if you’d like to do geocorrelation of some kind, I’ll be providing a version of the data with basic region-level lat/long information (limited to protect privacy) sometime in the next few days. Note: The ColorDB data is the main survey. The SatOnly data is the supplementary survey covering only the RGB faces in the map, and was presented on a half-black half-white background.)
And, of course, if you do anything fun with this data, I’d love to see the results—let me know at xkcd@xkcd.com.
xkcd 
Captchas are hard on the iPhone… This was grat to read. I have always been terrible with selecting colours. My mum said that when I was a child, they thought there was something wrong with me because I only ever painted in black.
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As mentioned above, I would also like to see the colorblind results as I’m colorblind and participated.
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Amazing work! Of course, a proportion of the women will be tetrochromats, giving them an unfair advantage. I’m wondering if there is an interaction with the just-noticable-distance: some colours appear more similar than others. Some studies suggest there is such an interaction:
http://theadventuresofauck.blogspot.com/2010/02/how-many-words-for-red-part-2.html
(I have data on the JND curve if you’d like to compare)
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When I first did the survey, I was surprised that it asked whether I had a Y chromosome or not, instead of asking gender. This showed that the Mr. Munroe recognized that sex and gender are not related. He was looking for data related to sex, not gender. In addition, this showed that he understood that chromosomal status does not necessarily indicate someone’s sex and that not all folks are XX or XY.
However, in his analysis, he made a leap to presume that sex and gender were the same thing. While it can be safe to say that the majority of folk are cisgender (their sex assigned at birth aligns with their gender identity), there is a large amount of people for which this is not true. Mr. Munroe jumped to conclusions and used inaccurate wording in his analysis. He should have reported the data he got, not the data he thought he got. He had no way to say any differences between men and women, since he did not ask about gender. Even though I am male, my answers when into the woman category in his analysis, which is blatantly false. You have no right to prescribe gender to my chromosomes nor anyone else’s. It is bad science as well as insulting.
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I couldn’t help myself…
sed ‘s/([a-z]*( [a-z]*){,1})[^#]*#([0-9a-f]{2})([0-9a-f]{2})([0-9a-f]{2})/ /’ rgb.txt | awk ‘{
red = echo 16i toupper($1) pq | dc
grn = echo 16i toupper($2) pw | dc
blu = echo 16i toupper($3) pw | dc
red | getline tmp1; close(red)
grn | getline tmp2; close(grn)
blu | getline tmp3; close(blu)
print tmp1 tmp2 tmp3 $4 $5
}’ > newrgb.txt
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amazing, loads of data visualized is so *sexy*
I’d totally be interested in seeing if the geo-data yields anything unexpected, gender didn’t make a lot of a difference apparently..
nice one!
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I’d have mentioned this by private email if I’d had it.
You are missing a label on the 3-face-RGB cube, in the lower right quadrant, between black and maroon.
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I’ve created two javascript 3d interactive visualisations of this data:
http://www.puremango.co.uk/2010/05/xkcd-colour-survey-results-visualisation/
And I hope to use the data for some more interesting things too 🙂
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I strongly recommend contacting Paul Kay at the University of California, Berkeley. He’s an emeritus professor of linguistics who has done an immense amount of research on languages and color naming.
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We’re getting ready to repaint our bedroom and the Mr. has requested that we paint it “WTF” (#3 on the guy list). What color is that?
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Things can be penis colored. Think fleshy pink.
I weep for those who can’t know this.
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What I thought would be interesting would be to see the range of (legitimate) answers to what a single color was. You could pick something very uncontroversial (Yellow) and/or something not quite one color (shades of pink/purple).
On another note, your fuchsia graph, while seeming to lack units, actually looks like there are pink areas at the intersections of the various borders — a neat effect I never expected to discover anywhere outside of a psychology textbook.
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@ Joshua Simeon Narins: that region is labeled. This is a cube, so the two edges intersect. That region is just more of the ‘brown’ region that crossed over the edge.
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Further note: Google has apparently updated their website and now correctly spells Fuchsia.
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@Alex – definitely, that line should read “I weep for my genetic sex.”
Since colorblindness is a recessive X-chromosome trait, it’s more common in genetic males (XY) in whom the recessive gene only has to be active on the one X-chromosome. In genetic females (XX), it has to be active on both X-chromosomes, so it’s much more rare.
I understand why the survey would select for people’s genetic sex, to gather data about color blindness, but it would have been interesting to know how a person’s gender identity affected their ability to name colors. I bet that would have had much more to do with whether people gave colors names like “dusky rose” or “penis”.
Also, it would have been interesting to discover a correlation between color blindness and gender variance, and to know how many gender-variant people read xkcd.
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This is wonderful. You have an amazing mind. (and maybe to much free time)
I love you no matter what color you are.
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It’s “Dusted Tomato”.
(+5 points if anybody gets the reference!)
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Maybe I’m missing something but how are those three sides more saturated than the others?
Other than that: A really cool thing! I should make one of those RGB cubes.
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1) To spell fuchsia correctly, note that the plant was named after Leonhart Fuchs.
2) Technically, you shouldn’t have asked whether your respondents had a Y chromosome, but rather how many X chromosomes they had. On the other hand, the prevalence of Turner syndrome (XO) or Kleinfelter’s syndrome (XXY) in your data set is likely to be minimal.
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@Joshua Simeon Narins:
The edges of the “missing quadrant” match up with each other. That little unlabeled section is the tiny corner of BROWN from the upper left.
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What I want to know is how tempting it was to occassionally serve an animated gif that slowly changed colour from one side of a colour boundary to the other. And whether this correlated to reports of readers destroying their monitors.
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Note also: “salmon” is totally a lie.
Girls know perfectly well that it’s PINK, guys just call it salmon so that they can try to justify wearing pink shirts.
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What color was “gay”? Did it cluster around pinkish shades, or was it just random?
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Here’s a compiled X11 rgb.txt based on your data:
http://pastebin.com/0dhY6Xc0
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First, I applaud mr xkcd for using assumed* chromosomes instead of gender or sex.
Second, I second Bentley & Jessica. I also have all the questions Jessica has. To the degree that I can start the data pool to answer some of those questions:
me = XX – male-identified – didn’t use the words Dusty, Butter, or Blush at all, but did use a variant of Dunno.
*One more point on the gender/sex/genes identity, most folks will assume their birth-identified sex corresponds with traditional genes, but based on sports genetics testing, this is occasionally a false assumption – http://www.google.com/search?hl=en&client=firefox-a&hs=Pyl&rls=org.mozilla%3Aen-US%3Aofficial&channel=s&q=xy+female+athletes&aq=f&aqi=&aql=&oq=&gs_rfai=
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Someone should really create an animated version of your dominant color name map, that just looks at one side of the cube and then moves through it. The borders would change and new color countries would form and grow. (I would make this but I wouldn’t know where to begin.)
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Penis? WTF?
What are the color values for those? I want to start a line of guy-centric paints.
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Which color was most popularly called “penis”?
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I remember doing this instead of paying attention to Aerodynamics class… And then going slowly insane to the point where I fled the classroom screaming and almost left my laptop in there.
I ended up getting so sick of the greens that everything became “green” and “more green” and “another fucking green”. Also, I seem to recall writing “rose or some girly shit” at some point. Lol.
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Sean:
The proportion of women who are possibly tetrachromats is extraordinarily small and probably should not be considered, just like how few people have more than two chromosomes. More importantly, it’s hard to test for tetrachromacy, because none of us would know how to tell whether or not we had it.
Mr. Munroe:
Perhaps you could have the posters made, charge for however much the actual cost is, plus the price of donating to a charity of your choice. Maybe it could be arranged to have a certain amount of these printed by charity, provided that all the profit went to organizations for the blind? I suppose it would be in poor taste, but then everybody wins.
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It would be really great if you created a survey to test color perception based on the results! (I know certain people who INSIST that a red-orange object is 100% red when it’s clearly more orange than red to me.)
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I literally laughed out loud for the “men’s popular colours”
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“Despite some requests, I’m not planning to make a poster of any of this, since it seems wrong to take advantage of all this volunteer effort for a profit;”
I knew I loved you before, but now I LOVE you!r
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I think mother-tongue would also skew results somewhat. In my own limited anecdotal surveys (after having received a decidedly *blue* t-shirt as a gift from my Israeli mother-in-law, purported to be green) – Hebrew- speakers will consistently put the divider between green and blue far more onto the blue side than English-speakers.
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You need a ‘share on facebook’ button.
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