I generated this using a Google API variable search tool developed by Eviltwin on #xkcd (I’m not linking to the tool so as to avoid potentially getting his API key revoked) Edit: He now offers the source and says it can be run without a key, and is happy to let people use it until Google does something. Not only is the API helpful in making these kinds of charts (which I spend more time doing than I care to admit), it also gives a roughly accurate count of results—in contrast to the Google search page.

The “number of results” count that Google gives when you search is clearly fabricated.  This is clear for a few reasons.  When Google says this:

You can tell that it’s wrong first by scrolling to the end of the results.  When you get to page 32, it suddenly becomes:

This doesn’t usually matter, since nobody looks much past the first few pages of results, but it’s annoying if you’re trying to use the number of results as a measure of something.  When I was making the Numbers comic, I didn’t use the API, and there were a few graphs I had to throw out, crop, or put on an unnecessary log scale; otherwise, Google’s clumsy number-fudging made the graphs look nonsensical.  I can’t find a good example now (perhaps they’ve smoothed it out a bit) but when searching for things like “I was born in <X>”, the results for successive years would look something like this:

… 150 : 200 : 250 : 300 : 350 : 117,000 : 450 : 251,000 : 500 : 550 : 312,000 : 320,000 : 390,000 : 425,000 …

If you scrolled to the last page for each, you’d find that the smaller counts were roughly accurate, but the counts in the hundreds of thousands had no more actual results than their neighbors.

I suppose it’s remotely possible that these numbers are correct, there are no years with an in-between number of hits, and for some reason they’re just not showing you most of the promised pages when you try to flip through them.  But making this even less likely is the fact that the search API (which is apparently being deprecated and replaced right now) doesn’t return these bad numbers—it gives reasonable-looking results which seem to be roughly consistent with the number you come up with by navigating to the last search page.

So it really looks like there’s a certain threshold of result volume beyond which Google apparently says “screw it” and throws out a gigantic number.  I imagine this is probably due to incompetence rather than intentional deception; I’m sure it’s hard to generate pages quickly from many sources, and maybe for searches with a lot of results they don’t have time to get it all synced up.  So they fudge the numbers.  The fact that this makes it look like they have way more results than they do is presumably just an unintended bonus.

All in all, this isn’t a big deal and I don’t think there’s anything particularly evil about it. It does make it hard to use Google hits as an accurate gauge of anything, but I suppose if you’re trying to study something by seriously analyzing Google result counts, you have bigger methodological problems to worry about.

Edit: As Mankoff observes, it looks like the API sometimes *underestimates* the number of results, too.  For example, it still reports 0 results for “narwhal zombie”, when a regular search shows quite a few. Now, I notice, scrolling through them, that most either have some minor character/text in between the two words, or are related to the comic I just posted.  But at least one seems to date back to last year.

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:

1. Dusty Teal
2. Blush Pink
3. Dusty Lavender
4. Butter Yellow
5. 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:

1. Penis
2. Gay
3. WTF
4. Dunno
5. 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.

Entre las muchas frases decidí destacar:

“Cuando el misterio es demasiado impresionante, es imposible desobedecer.”
Fuente: Capítulo II

…y de paso mi querida tira de xkcd

(lo siento pero nada de traducciones hoy)

El enlace de la original lo puedes encontrar aquí.

La traducción aproximada es algo como

Al dejar el ratón encima de las imágenes aparece un texto, esta vez si no se conoce un poco las demás tiras no tiene mucho sentido.
El texto que se puede leer en la versión española:

Debería usted hablar con la chica al final del pasillo, creo que le gustaría. Hágame saber si descubre por qué está comprando todas esas bolas de plástico coloradas.

Se refiere a esta tira de xkcd (en inglés y no tengo ganas de traducirla).

Detalles de otra tira cómica que sigo a menudo
Gracias a Baby Blues
Por Rick Kirkman y Jerry Scott

1.
- ¿Hammie me echarías una mano para hacer tu cama?
- ¿Porque?

2.
- En esta forma el trabajo se hará más rápido.
- No… Quiero decir ¿porque tenemos que hacer la cama desde un principio?

3.
- Pues, creo que NO TENEMOS…

4.
- ¡Siempre podríamos simplemente lanzar tus sabanas y mantas en el medio de la cama y dejarte hacer una madriguera como un roedor!

5.

6.
- Si él puede hacerlo, YO TAMBIEN!

Entonces necesitas más desafíos en tu vida… ¿es eso lo estas intentando decir en este momento, Wanda?

El que quiera ver entradas anteriores mías de Baby Blues lo puede hacer por una entrada que tengo Baby Blues y sus verdades

Traducción un poco mala y rápida, pero creo que se entienda bastante:

PASO MUCHO TIEMPO MENTALMENTE COREOGRAFIANDO COMPLICADAS ESCENAS DE LUCHA CON LOS EXTRANEOS QUE ME RODEAN.

– Ok . Si ese anciano saca una ballesta,
– le tiro la pesa de correo y me refugio atrás de la maquina de sellos.
– Pero y si la chica cerca de la puerta tiene una katana en esa caja?
– Mejor poner mi iPod con el tema de lucha de “Kill Bill”, simplemente por sea caso.

Al dejar el ratón sobre la imagen de la página oficial, como es su solito aparece una frase:
That track (‘Battle Without Honor or Humanity’) — like ‘Ride of the Valkyries’ — improves *any* activity.
Que traducida es algo como:

La canción (‘Battle Without Honor or Humanity’) — como ‘Ride of the Valkyries’ — mejora *cualquiera* actividad.

Police reported three dozen cheerful bystanders, yet no one claims to have seen who did it.

Que traducido rápidamente y con faltas de ortografía es algo como:

La policía ha reportado una docena de testigos oculares contentos, pero se confirma que nadie ha visto nada

Estoy seriamente pensando en imprimir el famoso pdf y tener siempre una copia conmigo.

Floor Tiles

- Porque andas raro?
Pensando – Pues, mi instinto es de pisar solo las casillas negras, pero están demasiado lejos entre ellas. Entonces me muevo por las casillas que están directamente en linea con las negras, pero eso quiere decir que cuando nos movemos en diagonal tengo que utilizar un patrón donde…
- YO NO ANDO RARO.

Si dejas el ratón encima de la imagen aparecerá una frase del autor que traducida es:

La parte peor es cuando la acera está fuera de sincronía con tu paso natural.