Best of Rationality Quotes, 2012 Edition
post by DanielVarga · 2013-01-26T03:03:20.330Z · LW · GW · Legacy · 18 commentsContents
18 comments
I finished creating the 2012 edition of the Best of Rationality Quotes collection. (Here is last year's.)
Best of Rationality Quotes 2012 (500kB page, 434 quotes)
and Best of Rationality Quotes 2009-2012 (1200kB page, 1140 quotes)
The page was built by a short script (source code here) from all the LW Rationality Quotes threads so far. (We had such a thread each month since April 2009.) The script collects all comments with karma score 10 or more, and sorts them by score. Replies are not collected, only top-level comments.
As is now usual, I provide various statistics and top-lists based on the data. (Source code for these is also at the above link, see the README.) I added these as comments to the post:
- Top quote contributors by total karma score collected
- Top quote contributors by karma score collected in 2012
- Top quote contributors by statistical significance level (See this comment for a description of this metric.)
- Top original authors by number of quotes
- Top original authors by total karma score collected
18 comments
Comments sorted by top scores.
comment by DanielVarga · 2013-01-25T12:54:08.268Z · LW(p) · GW(p)
Top original authors by number of quotes. (Note that authors and mentions are not disambiguated.)
- Feynman 28
- Russell 26
- Pratchett 18
- Nietzsche 18
- Heinlein 18
- Einstein 15
- Dawkins 14
- Chesterton 12
- Wilson 11
- Johnson 11
- Asimov 11
- Taleb 10
- Dennett 10
- Darwin 10
- Voltaire 9
- Meier 9
- Hume 9
- Clark 9
- Buffett 9
- Neumann 8
- Thoreau 7
- Rochefoucauld 7
- Peirce 7
- Medawar 7
- Keynes 7
- Huxley 7
- Gould 7
- Dijkstra 7
- Aristotle 7
- Yudkowsky 6
- Plato 6
- Orwell 6
- Munroe 6
- Mencken 6
- Marx 6
- Marshall 6
- Lichtenberg 6
- Kant 6
- Jaynes 6
- Holmes 6
- Hitler 6
- Egan 6
- Drexler 6
- Descartes 6
- Carlyle 6
- Binmore 6
↑ comment by DanielVarga · 2013-01-25T12:58:08.860Z · LW(p) · GW(p)
Top original authors by karma collected.
- 454 Russell
- 392 Chesterton
- 365 Pratchett
- 322 Feynman
- 214 Nietzsche
- 196 Friedman
- 190 Heinlein
- 190 Dennett
- 183 Sagan
- 172 Voltaire
- 169 Wilson
- 162 Friedrich
- 157 Egan
- 149 Darwin
- 144 Moldbug
- 138 Plato
- 137 Einstein
- 134 Dawkins
- 133 Buffett
- 129 Aristotle
- 127 Aaronson
- 125 Marcus
- 124 Kahneman
- 123 Mencken
- 123 Asimov
- 122 Orwell
- 119 SMBC
- 119 Johnson
- 117 Hitler
- 117 Descartes
- 113 Kaas
- 110 Taleb
- 109 Hume
- 108 Confucius
- 103 Godin
- 102 Keynes
- 99 Stephenson
- 98 Munroe
comment by DanielVarga · 2013-01-25T12:49:47.988Z · LW(p) · GW(p)
Top quote contributors by total karma score collected:
- 1223 RichardKennaway
- 854 gwern
- 735 Rain
- 715 MichaelGR
- 637 Eliezer_Yudkowsky
- 618 GabrielDuquette
- 584 Alejandro1
- 560 anonym
- 551 Konkvistador
- 529 Jayson_Virissimo
- 485 lukeprog
- 458 NancyLebovitz
- 415 RobinZ
- 408 Yvain
- 374 CronoDAS
- 350 James_Miller
- 342 Tesseract
- 310 Grognor
- 308 Alicorn
- 297 DSimon
- 283 Stabilizer
- 280 peter_hurford
- 270 Nominull
- 258 billswift
- 253 Oscar_Cunningham
- 244 arundelo
- 239 Eugine_Nier
- 235 Kutta
- 234 Thomas
- 224 [deleted]
- 191 roland
- 189 Kaj_Sotala
- 178 Maniakes
- 177 J_Taylor
- 160 katydee
- 160 cousin_it
- 155 Will_Newsome
- 151 djcb
- 150 Nic_Smith
- 148 MinibearRex
↑ comment by DanielVarga · 2013-01-25T12:51:07.619Z · LW(p) · GW(p)
Top quote contributors by statistical significance level:
- 0.00003 (20.14 in 29): Alejandro1
- 0.00005 (19.31 in 32): GabrielDuquette
- 0.00014 (28.11 in 9): Oscar_Cunningham
- 0.00020 (25.45 in 11): peter_hurford
- 0.00119 (47.50 in 2): Delta
- 0.00127 (18.55 in 22): Yvain
- 0.00136 (17.06 in 31): Jayson_Virissimo
- 0.00219 (62.00 in 1): Solvent
- 0.00394 (18.00 in 19): Tesseract
- 0.00544 (22.25 in 8): Maniakes
- 0.00620 (56.00 in 1): RomeoStevens
- 0.00777 (30.00 in 3): benelliott
- 0.00882 (35.00 in 2): michaelkeenan
- 0.00936 (24.40 in 5): Ezekiel
- 0.01276 (45.00 in 1): Mycroft65536
- 0.01296 (33.00 in 2): summerstay
- 0.01563 (15.91 in 22): James_Miller
- 0.01713 (43.00 in 1): alex_zag_al
- 0.01713 (43.00 in 1): Liron
- 0.01968 (41.00 in 1): Andy_McKenzie
- 0.02114 (40.00 in 1): bentarm
- 0.02350 (13.61 in 54): Rain
- 0.02414 (29.50 in 2): gRR
- 0.02435 (19.57 in 7): fortyeridania
- 0.02727 (19.29 in 7): Unnamed
- 0.02733 (15.63 in 19): DSimon
- 0.02850 (15.88 in 17): Nominull
- 0.02851 (15.72 in 18): Stabilizer
- 0.03630 (18.00 in 8): wallowinmaya
- 0.03746 (19.17 in 6): Mark_Eichenlaub
- 0.03938 (13.24 in 54): MichaelGR
- 0.04005 (23.00 in 3): cata
- 0.04005 (23.00 in 3): tingram
- 0.04309 (22.67 in 3): Oligopsony
- 0.04394 (14.76 in 21): Grognor
- 0.04752 (17.86 in 7): VKS
- 0.04766 (25.00 in 2): Automaton
- 0.04922 (19.20 in 5): Lightwave
- 0.05288 (16.09 in 11): J_Taylor
- 0.05729 (21.33 in 3): Miller
↑ comment by DanielVarga · 2013-01-25T12:50:09.932Z · LW(p) · GW(p)
Top quote contributors by karma score collected in 2012:
- 452 GabrielDuquette
- 451 Alejandro1
- 396 Konkvistador
- 339 Jayson_Virissimo
- 309 gwern
- 306 lukeprog
- 289 NancyLebovitz
- 259 Grognor
- 243 Stabilizer
- 200 Alicorn
- 181 James_Miller
- 179 peter_hurford
- 175 arundelo
- 174 Eugine_Nier
- 151 Oscar_Cunningham
- 143 katydee
- 137 fortyeridania
- 136 [deleted]
- 128 Will_Newsome
- 125 VKS
- 117 J_Taylor
- 112 Stephanie_Cunnane
- 111 Mark_Eichenlaub
- 110 army1987
- 109 wallowinmaya
- 103 Ezekiel
- 101 RichardKennaway
- 97 Eliezer_Yudkowsky
- 95 Delta
- 88 Yvain
- 87 baiter
- 85 MBlume
- 82 Nominull
- 79 chaosmosis
- 78 roland
- 72 Vaniver
- 72 paper-machine
- 71 taelor
- 70 scmbradley
- 69 tingram
comment by ygert · 2013-01-25T13:48:57.269Z · LW(p) · GW(p)
The link to this year's best of collection is giving me a 404 Not Found error. The 2009-2012 collection is accessible however.
Replies from: DanielVarga↑ comment by DanielVarga · 2013-01-25T14:03:35.856Z · LW(p) · GW(p)
Fixed, thanks!
comment by taserian · 2013-02-01T14:43:19.801Z · LW(p) · GW(p)
Thank you for the data and collections of quotes! However, the link to the source code is pointing to the directory where you have the html files for the 2012 and 2009-2012 "Best of" collections, not to any .zip or .gz of the source code itself, and it seems to be pulling up a default page with the unstyled HTML version of the 2012 collection.
Replies from: DanielVarga↑ comment by DanielVarga · 2013-02-02T17:51:01.455Z · LW(p) · GW(p)
I removed the broken index.html, sorry. Now you can see the whole (messy) directory. The README is actually a list of commands with some comments, the source code consists of parse.py and convolution.py.
comment by Shmi (shminux) · 2013-01-25T18:57:50.660Z · LW(p) · GW(p)
Neat. Does the quote karma follow something like the exponential distribution?
Replies from: gwern, DanielVarga↑ comment by gwern · 2013-01-25T19:51:18.628Z · LW(p) · GW(p)
I tried some stuff in R. While it looks exponential, none of the code or fitting functions gave good results on the highest-karma quotes - I guess because all the other thousand quotes look so linear. Of course, I could have just messed up in any of the following:
Open http://people.mokk.bme.hu/~daniel/rationality_quotes_2012/rq.html in Firefox; C-a; then:
$ xclip -o | grep Permalink | grep points | cut -f 1 -d' ' | tr '\n' ','
$ R
R> karma <- sort(c(105,73,66,64,63,62,60,60,58,58,57,57,57,57,57,56,56,55,55,54,53,51,50,50,49,49,
48,48,48,47,47,46,46,45,45,44,44,44,43,43,43,43,43,43,43,43,43,42,42,41,41,41,
41,41,40,40,40,40,39,39,38,38,38,38,38,38,38,38,37,37,37,37,37,37,37,37,36,36,
36,36,36,36,36,35,35,35,35,35,34,34,34,34,34,34,34,34,34,34,34,34,34,34,33,33,
33,33,33,33,33,32,32,32,32,32,32,32,32,32,32,32,32,32,31,31,31,31,31,31,31,31,
31,31,31,31,31,30,30,30,30,30,30,30,30,30,30,30,29,29,29,29,29,29,29,29,29,29,
29,29,29,29,29,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,27,27,
27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,26,26,26,26,26,26,
26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,25,25,25,25,
25,25,25,25,25,25,25,25,25,25,25,25,25,25,24,24,24,24,24,24,24,24,24,24,24,24,
24,24,24,24,24,24,24,24,24,24,24,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,
23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,22,22,22,22,22,
22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,
22,22,22,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,
21,21,21,21,21,21,21,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,
20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,19,19,19,19,19,19,19,
19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,
19,19,19,19,19,19,19,19,19,19,19,19,18,18,18,18,18,18,18,18,18,18,18,18,18,18,
18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,
18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,17,17,17,17,17,17,17,17,17,17,17,
17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,
17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,
17,17,17,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,
16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,
16,16,16,16,16,16,16,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,
15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,
15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,14,14,14,14,14,
14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,
14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,
14,14,14,14,14,14,14,14,14,14,14,14,14,13,13,13,13,13,13,13,13,13,13,13,13,13,
13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,
13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,
13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,12,12,12,12,12,12,
12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,
12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,
12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,
12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,
11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,
11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,
11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,
11,11,11,11,11,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,
10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,
10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,
10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10))
R> summary(karma)
Min. 1st Qu. Median Mean 3rd Qu. Max.
10.0 12.0 17.0 19.5 23.0 105.0
R> n <- seq(length(karma))
R> temp <- data.frame(y = karma, x = n)
# first try, fitting a nonlinear model
R> plot(temp$x, temp$y)
R> mod <- nls(y ~ exp(a + b * x), data = temp, start = list(a = 0, b = 0))
R> lines(temp$x, predict(mod, list(x = temp$x))); mod
Nonlinear regression model
model: y ~ exp(a + b * x)
data: temp
a b
1.9094 0.0016
residual sum-of-squares: 17684
Number of iterations to convergence: 9
Achieved convergence tolerance: 8.9e-06
# second try, fitting a quadratic
R> lm(temp$y ~ temp$x + I(temp$x^2))
Call:
lm(formula = temp$y ~ temp$x + I(temp$x^2))
Coefficients:
(Intercept) temp$x I(temp$x^2)
1.33e+01 -1.91e-02 3.96e-05
# third try, log transform
R> exp(fitted(lm(log(temp$y) ~ temp$x)))
....
1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134
35.080 35.123 35.167 35.211 35.255 35.299 35.343 35.387 35.431 35.475 35.520 35.564 35.608 35.653
1135 1136 1137 1138 1139 1140
35.697 35.742 35.786 35.831 35.876 35.920
# fourth and final try, log variation
R> cc <- coef(lm(log(temp$y) ~ temp$x)); cc
(Intercept) temp$x
2.160310 0.001246
R> with(temp, fitted(nls(y ~ exp(a + b*x), start = list(a = cc[1], b = cc[2]))))
...
[1106] 39.594 39.657 39.721 39.784 39.848 39.912 39.976 40.040 40.104 40.168 40.232 40.297 40.361
[1119] 40.426 40.491 40.556 40.620 40.686 40.751 40.816 40.881 40.947 41.012 41.078 41.144 41.210
[1132] 41.276 41.342 41.408 41.474 41.541 41.607 41.674 41.740 41.807
attr(,"label")
[1] "Fitted values"
↑ comment by DanielVarga · 2013-01-25T19:59:58.193Z · LW(p) · GW(p)
It is roughly exponential in the range between 3 and 60 karma.
You can find the raw data here.
Edit: I didn't spot gwern's more careful analysis. I am still digesting it. gwern, you should use the above link, it contains the below-10 quotes, too.
Replies from: gwern↑ comment by gwern · 2013-01-25T20:49:54.490Z · LW(p) · GW(p)
The extra data doesn't seem to make much difference:
R> karma <- read.table("http://people.mokk.bme.hu/~daniel/rationality_quotes_2012/scores")
R> karma <- sort(karma$V2)
R> summary(karma)
Min. 1st Qu. Median Mean 3rd Qu. Max.
-8.0 4.0 8.0 10.7 15.0 105.0
...
Nonlinear regression model
model: y ~ exp(a + b * x)
data: temp
a b
-0.01088 0.00134
residual sum-of-squares: 22772
Number of iterations to convergence: 7
Achieved convergence tolerance: 3.59e-06
It is roughly exponential in the range between 3 and 60 karma.
Eyeballing it, looks like the previous fit crosses around 40.
R> karma <- karma[karma<40]
...
Nonlinear regression model
model: y ~ exp(a + b * x)
data: temp
a b
-0.01088 0.00134
residual sum-of-squares: 22772
Number of iterations to convergence: 7
Achieved convergence tolerance: 3.59e-06
The fit looks much better:
Replies from: DanielVarga↑ comment by DanielVarga · 2013-01-25T21:06:02.432Z · LW(p) · GW(p)
I am afraid I don't understand your methodology. How is a rank versus value function supposed to look like for an exponentially distributed sample?
Replies from: gwern↑ comment by gwern · 2013-01-25T21:08:38.089Z · LW(p) · GW(p)
How else would you do it?
Replies from: DanielVarga, shminux↑ comment by DanielVarga · 2013-01-25T22:29:57.231Z · LW(p) · GW(p)
When I stated that the middle is roughly exponential, this was the graph that I was looking at:
d <- density(karma)
plot(log(d$y) ~ d$x)
I don't do this for a living, so I am not sure at all, but if I really really had to make this formal, I would probably use maximum likelihood to fit an exponential distribution on the relevant interval, and then Kolmogorov-Smirnoff. It's what shminux said, except there is probably no closed formula because the cutoffs complicate the thing. And at least one of the cutoffs is really necessary, because below 3 it is obviously not exponential.
↑ comment by Shmi (shminux) · 2013-01-25T21:19:21.166Z · LW(p) · GW(p)
I expected something like this or the section thereafter.