The words of the numbers
Encouraged by this news, I made my own analysis of the last budget’s speech by Alistair Darling.
First I recreated the face of Mr. Darling with the data suggested. As usual the size of the words is proportional to the repetition.
Later, using my own text analysis over the last eleven budget’s speeches, I made different visualizations showing distance’s relationship and the evolution of the most used, or most significative, words.
The last one is focused in the word ‘tax’. In this case the distance to the words is the average distance in the speeches. The big one represent all years from 2005 to 2010. The other two are focused in their own year.
Due to the filesize I recomend you to download and navigate the PDF version.
Dwonload PDFÂ JO-D-100411-Budget2010-ENG (621kB)
The Words Of Jesus
Since we are in Easter I think it’s time to answer an email that Luis Barcelo sent to me a month ago. He suggested about an image only with the words that Jesus said.
Great idea!, but how to find what Jesus was recorded as saying?. Well this hard work is already done by JB Phillips as you can see in this website. He has the New Testaments books with the Jesus words in red. Easy task, isolate these words by using the select by format of any text processing application and we are done.
For the curious the beginning of the my counted words list with ALL the words: the (836), you (626), and (546), to (430), of (349), i (305), is (278), that (223), will (216), your (215), who (209), in (203), for (191), it (187), a (185), have (174), not (168), me (164), are (163), be (153), but (151), man (141), what (120), he (118), my (116), do (113), come (108), has (101), him (98), his (94), father (91), god (89), they (88), go (84), from (82), this (79), if (78), one (77), as (74), can (71), all (66), no (66), on (66), say (64), them (64), know (62), believe (61), up (61), with (60), am (58), when (56), life (53), out (51), give (50), into (50), or (50), see (50), son (49), how (47), so (47), good (46), then (46), which (46), at (45), must (45), those (45), by (43), now (43), like (42), heaven (41), there (41), men (40), own (38), hear (35), never (35), things (35), tell (34), their (34), was (34), don’t (33), let (33), shall (33), because (32), people (32), sent (32), does (30), eye (30), kingdom (28), make (28), day (27), even (27), live (27)…
From this list we will remove all the single characters words and ‘the’, ‘to’, ‘of’ and ‘and’. Sometimes I also remove ‘you’ because of the big distance between this one and the rest of words.
You can Download the full list here: thewordsofjesus.
The other problem is the base image. Which one?. Luis send me an image from the movie The Passion, and I made a couple of images using it. Take a look.
Download PDFÂ JO-D-100328-JesusWords01-ING (254kB)
Download PDFÂ JO-D-100328-JesusWords02-ING (390kB)
Download PDFÂ JO-D-100328-JesusWords03-ING (541kB)
But I want to go further.
The only change to find a ‘real’ image of Jesus is the The Holy Shroud of Turin. And we have a useful reconstruction, a painting created in 1935 by an Armenian artist named Ariel Aggemian. There is a funny history that joins this image, computers and an indian spiritual master. I retouched it a little bit in order to have a sharp result as base image.
As final step let me choose a representative font. The first modern print of the Biblia was made in 1454 by Gutenberg and we have a very nice free font that mimics that print here.
We have all ingredientes!. So, here we go…
Download PDFÂ Â JO-D-100328-JesusWords04-ING (372kB)
I also made another testing files I want to share.
Download PDF JO-D-100328-JesusWords05-ING (148kB)
Download PDFÂ JO-D-100328-JesusWords06-ING (372kB)
That’s all!. I have several ideas about this matter but not enough free time. So may be next time.
Hope you like it.
On the Origin of Words
A portrait of Darwin with the most used words in the book “On the Origin of Species”.
Word list: species (1874), forms (895), natural (874), different (829), one (816), may (657), case (653), many (609), selection (595), can (585), plants (575), varieties (575), organs (570), animals (555), parts (507), two (470), great (422), several (406), conditions (389), distinct (387), thus (384), characters (378), generally (370), period (363), number (360), structure (357), certain (354), groups (351), life (339), existence (334), facts (325), change (320), individuals (314), long (314), much (312), first (307), important (306), see (305), variations (300), crossed (299), common (295), now (292), new (291), produced (289), closely (286), birds (284), time (284), even (279), become (278), developed (277), must (275), inhabitants (274), related (269), instance (262), often (262), large (260), degree (258), domestic (251), flowers (250), mr (250), modification (249), believe (247), breeds (242), islands (242), less (240), widely (233), modified (232), well (231), genera (230), use (230), habits (229), insects (228), state (228), though (228), another (227), formations (227), seeds (226), probably (224), appear (223), far (223), perfect (223), present (222), slight (222), descendants (221), class (219), yet (219), remarked (216), almost (214), living (212), might (212), hybrids (211), like (211), nearly (203), extinct (200), manner (198), parent (198), instincts (197), sterility (196), found (183), effects (182), variability (182), view (182), inherited (181), cause (180), country (180), successive (180), whole (179), vary (178), water (178), intermediate (177), doubt (176), highly (176), supposed (176), increase (175), seems (173), given (172), place (172), genus (171), formerly (169), kind (169)…
There is a huge difference between ‘Species’ and the rest of the words, so I discard it for the spread process but you still can find it in the title with appropiate size.
If you are interesting in the complete list send me an email asking for it and I will send it to you.
Rotated version.
Detail view.
Download PDFÂ JO-D-100325-Darwin (428KB)
Download PDFÂ JO-D-100325-Darwin-Rot (614kB)
Miguel Delibes
As a tribute to this great writer, recently died. This time, words and images only in spanish.
A closer look.
For the picture I counted all the words used in some of his best books: Cartas de un sexagenario voluptuoso, Cinco horas con Mario, Diario de un cazador, Dos viajes en automovil a Suecia y los Paises Bajos, El amor propio de Juanito Osuna, El camino, El hereje, El mundo en la agonia, El principe destronado, España 1936-1950 Muerte y resurreccion de la novela, La hoja roja, La mortaja, La partida, La sombra del cipres es alargada, Las ratas, Los santos inocentes, Señora de rojo sobre fondo gris, Tres pajaros de cuenta y tres cuentos olvidados, Viejas historias de Castilla la Vieja.
A list of most-used words: casa (1662), don (1568), hombre (1560), paso (1420), miraba (1416), cosas (1338), mano (1220), niño (1098), sentÃa (997), hijo (971), bueno (937), dejó (925), salió (923), llegó (917), parece (909), vida (902), bien (894), ojos (892), viejo (891), hablar (880), luego (856), entonces (845), pensó (837), madre (828), cabeza (810), ver (806), volvió (786), tarde (757), aquella (755), padre (753), tiempo (749), quedó (742), cipriano (726), parte (715), mal (683), pueblo (678), dice (666), podÃa (665), noche (661), primera (661), quiere (652), llevaba (645), vivir (642), creo (638), chica (636), medio (623), preguntó (616), siempre (601), usted (589), tomó (577), muerte (566), hermana (554), aún (551), mario (547), palabras (531), digo (527), ponÃa (523), debe (519), veces (519), iba (516), lado (515), voz (512), señorito (511), cuenta (510), muchacha (502), mundo (501), calle (496), tal (496), verdad (492), pues (490), quico (490), libro (478), llamó (473), levantó (471), mujer (471), conocÃa (470), dios (470), puerta (465), aquà (463), juan (459), doña (456), mamá (456), junto (453), esperaba (451), momento (450), nunca (449), último (446), mejor (444), mar (438), gusto (437), puso (437), fin (436)…
Probably my nicer list so far…
Download PDF Â Â JO-D-100315-MiguelDelibes (281kB)
Also, I made the version with words rotated.
Download PDFÂ Â JO-D-100315-MiguelDelibes_R (188kB)
Thank you Miguel…
Freddie Mercury
Following the suggeston posted by Mohamed Magdy about the Queen Image, here you have a Freddie Mercury portrait with the most used words of his songs.
A closer look.
Download PDF JO-D-100310-Freddie-ENG (205kB)
Kurt Cobain
We are talking about music again. Now we will look at Nirvana lyrics. Kurt Cobain portrait as base imagen.
Most used words: like (63), go (48), take (45), want (40), yeah (39), make (36), never (36), can (34), know (33), get (32), just (32), hey (31), got (30), one (30), see (30), oh (29), say (29), happy (28), way (28), heart (27), think (24), find (23), something (23), day (22), night (21), time (21), come (20), die (20), eyes (20), now (20), shame (20), wish (20), away (19), friend (19), new (19), said (19), love (18), back (16), dive (16), hurts (16), else (15), feel (15), nothing (15), pick (15), ain’t (14), cross (14), kiss (14), light (14), mean (14), cold (13), help (13), hung (13), keep (13), look (13), sun (13), wait (13), another (12), eat (12), face (12), fun (12)…
More information about Nirvana and Kurt Cobain in Wikipedia.
Download free pdf (for non comercial use):
JO-D-100301-Nirvana-ENG.pdf (173kB)
Freddie Mercury words
The most used words in Queen lyrics. The base image is the cover art of one of their albums.
Thank you Freddie…
Download JO-D-100301-Queen-ENG.pdf (205kB)
Files free for non commercial use.
Obama Words Relationship
Obama speeches are a good testing ground. This time we are going to investigate the relationship between some of the most ‘representative words’ used in his speeches. These words are: american, can, country, hope, iraq, people, schools, war, work and world. You can find the Obama Speeches in this url http://obamaspeeches.com/
The words cloud image represents the words close to one of the ‘representative word’ (in color). Word size represents the number of times the word appears. The distance to the ‘representative word’ represents the average distance of all instances of each word.
Take a closer look.
The last image represents all the words with a proportional size and an evolution in time of the most used words. Also, there is an attempt to count only the adjetives (it is just an experiment!), because, in some way, adjetives ‘describe’ things.
You can download and distribute my images for free (for non commercial use).
Download PDF ObamaDistances.pdf (8.5MB)
Download PDFÂ ObamaEvolutiom.pdf (385kB)
Remember my other post related to Obama. The Obama Speeches Portrait, and the Obama Tree.
Zapatero and Rajoy
Just a quick post showing another point of view of the last congressional debate in Spain.
It is a little bit hard to compare, because Zapatero speak much more than Rajoy (17935 / 4702 words).
Speeches from http://www.congreso.es/.
Download free JO-D-100224-ZapateroRajoy-ESP.pdf (283kB)
Jack VS Locke
Animated by a suggestion of ^BadNumber^ from lostzilla.net here we go again with… Lost.
This time I have analyzed all the dialogues of the five seasons, but thanks to the scripts hosted in lostpedia.wikia.com we can know the words each character said… exactly.
So here are the results. The first image is a versus between Jack and Locke. Each face has the words correspondig to the character.
In the last image each character has his own words. The bigger the more times they used it. The distance to the character is mostly random. We choose nine of them… look at it and you will know why.
As a curiosity take a look to number of times each character talk, the number of words spoken and the average words per intervention.
jack (3254 int / 28951 words / 8.89 avg)
locke (2339 int / 22670 words / 9.69 avg)
hurley (1761 int / 17244 words / 9.79 avg)
kate (2272 int / 17327 words / 7.62 avg)
sawyer (2387 int / 24165 words / 10.12 avg)
sayid (1505 int / 14754 words/ 9.80 avg)
ben (1009 int / 13064 words / 12.4 avg)
juliet (924 int / 8661 words / 9.37 avg)
desmond (868 int / 8413 words / 9.69 avg)
I want to thank ^BadNumber^ and cesarfuenla for their assistance with ideas and suggestions. Thank you guys… hope you like it.
Download free PDF jackvslocke.pdf (578kB)
Download free PDF lost_thewordstheysaid.pdf (6.5MB)
As a bonus… the ‘dark’ version…
Download free PDF jackvslocke-dark.pdf (189kB)
You can print it freely (for non commercial use), but if you prefer a big size printed copy you can order it in deviantart:
Jack vs Locke
Lost The Words They Said
Jack vs Locke Dark Version
Millenium Characters
Once again we will work with Millenium trilogy, the Stieg Larsson Bestsellers.
This time I covered the three books searching relationships between some of the main characters and the words around it.
Word size represents the numbre of times the word appears. The distance to the name represents the average distance of all instances of the each word.
Download PDF MilleniumCharacters-ENG.pdf (4.5MB)
Take a closer look.
John Maeda
Just a quick post about John Maeda and his book ‘ Laws of Simplicity” wich I recommend reading.
The image contains the most used words in this book.
And, of course, thanks John because you began processing….
Download free PDF JohnMaeda.pdf (580kB).
Take a closer look.
Lost Characters.
We are Lost again. Now we will look at the Characters evolution and their relationship.
I took all the english subtitles of the five seasons and I counted all the words but in a new and different way, by taking care of word position.
The right part of the image shows the number of times the word appears through episodes. You can see how some characters just disappear or gain prominence in time.
In the left part of the image, every character has the words that are close to his name in the subtitles. The bigger, the more times the word appears. The distance to the character is proportional to the distance between words. Characters are colored in order to ease location. The character position is random.
You can draw some conclusions.
Take a closer look….click to enlarge.
Hope you like it!
Download PDF poster LostCharacters.pdf (883kB).
The Bible
Probably the most interesting book ever… The Holy Bible.
This time I want to know if there is deep differences between New and Old Testaments. So I counted words from these documents independently and put the results together each one in a side of the image. The left hand represents the words from the New Testament. The right hand the Old Testament ones.
Because the Old testament is bigger than the New Testament I used a correction factor so the words can be compared in size between both documents.
As base image I used a part of a well know Michelangelo painting…
One more thing. There is a lot of free versions of the Bible. I just pick one of them in english and another in spanish (double work of course). There must be huge differences between all the different versions of the Bible. Even between the differents idioms. For example the word ‘Lord’ in english correspond to ‘Jehovah’ in the spanish version… I don’t know why…
And remember, it is just a exercise… the results may be inexactly or totally wrong at all..
Old Testament: lord 7279, god 3340, son 3044, said 2941, king 2759, upon 2502, israel 2501, day 2124, house 1943, people 1910, man 1829, land 1709, hand 1681, children 1662, saying 1628, came 1590, shalt 1510, come 1432, one 1431, go 1342…
New Testament: god 1392, said 1061, jesus 984, man 908, saying 904, things 848, lord 734, come 657, one 615, also 599, christ 573, came 506, day 485, son 454, father 428, now 407, men 396, therefore 356, know 348, went 338…
Download TheBible.pdf (English Version) (436kB)
Download LaBiblia.pdf (Spanish Version) (440kB)
Gilmore Girls
Yes, I know… after seven seasons the show is over but it is so funny and the words are important within so many fast dialogues…
So I decided to collect all the words of the seven seasons with this result:
rory 2931, thank 2678, mom 2096, sorry 1964, luke 1877, guys 1805, lorelai 1566, nice 1469, kid 1112, dad 962, paris 881, hello 851, dinner 848, coffee 807, tonight 752, stuff 727, tomorrow 657, gilmore 644, date 643, sookie 643, lane 629, kirk 628, dean 624, logan 572, late 571, hate 551, perfect 546, married 540, emily 534, richard 512, taylor 510, excuse 505, drink 494, yale 491, crazy 478, jess 474, parents 473, phone 473, weird 468, grandma 463…
Perhaps some of them are part of the four final words that we are still waiting for…
And what about Lauren Graham?… as lovely in person as being Lorelai Gilmore.
Get Lost…
We are close to the last season of Lost. It’s time to review all the words used in the last 5 seasons… perhaps we can find a clue about the end of the story…
First words: jack 906, sorry 578, john 547, thank 465, guy 403, kate 372, hell 371,locke 342, sayid 328, claire 282, ben,280, charlie,270, sawyer,269, dude 267, walt 203, damn 196, michael 196, beach 192, hurley 184, hello 180, jungle 172, dad 171, desmond 155, trust 153, jin 152, juliet 152, crash 150, anyone 147, ain’t 145, kid 143, hurt 142, worry 140, hugo 139, nice 137, hatch 136, whatever 135, real 131, camp 130, excuse 129, stuff 120…
As you can see Jack is the first one… but I believe that John is the true soul of the show… it had to be you John Locke…
Juan Carlos I christmas speeches
The most commonly used words in the 34’s Christmas speeches of King Juan Carlos I, from 1975 to 2008.
First 20 words: españa 244, españoles 236, debemos 186, familia 143, paz 130, esfuerzo 118, mejor 117, unidad 104, futuro 102, social 98, sociedad 98, pueblo 92, mayor 90, nuevo 86, trabajo 84, común 82, económica 82, constitución 81, deseo 81, paÃs 80…
This time only spanish version.
Radiohead
Words from 89 Radiohead lyrics and a Thom Yorke photo.
Most used: get 73, can 67, like 58, just 57,come 53, got 52, want 46, go 38, one 38, try 38, feel 36, eyes 34, nothing 34, back 33, now 31, everything 30, know 30, take 30, run 27, stand 27, head 26, never 26, see 25, think 25, better 24, case 24, best 23, things 23, time 23, man 22, wish 22, even 21, happen 21, little 21, sit 21, turn 21, world 21, end 19, love 19…
Download PDF radiohead-eng.pdf (190kB)
Obama tree.
We will go a step forward from this Obama Post. Remember in that case I counted all the words in more than one hundred Obama speeches.
Using the same data I made a new algorithm based on a simple tree structure but, in this case, the branches are the words.
The tree structure is highly random, but the size o the words (branch width) is always proportional to the number of times the word appears in the speeches.
The image contains four samples with different color variations. The branches take their color from the original Obama photo post. I added some transparency so the overlap generates more color variations.
The algorithm generates a new random version of the tree every time I click. So I just clicked till I obtained a nice one and then saved it as pdf.
Download obama-tree.pdf 5.34MB
Also take a look at this other version. Generated using the Van Gogh Image results.
Hope you like it!.
Jester in words.
Marillion was one of my favorites bands… while Fish was in there.
In the Fish era all the albums covers was made by Mark Wilkinson. Really beatifull drawings that match perfectly with the introspective songs lyrics.
Let’s go. I mix both concepts counting all the words from Marillion (with Fish) lyrics and one of their album covers.
The first most used words: know 80, just 67, heart 52, time 47, got 43, way 41, now 39, eyes 38, never 37, say 34, another 33, love 33, go 32, take 31, like 30, night 30, away 29, tux 29, want 28, burning 27.
Download PDF version. (347kB).
Download (white) PDF version. (347kB). (see png)
(Dedicated to Rafa, Chavo and Pez… so, so, so close to forty)
Hey Boss…
Words from more than four hundred Bruce Springsteen lyrics. This time the word size is proportional to the number of times the word appears in his songs.
The list: just 733, well 720, night 667, baby 650, come 650, got 621, love 604, now 582, like 516, man 484, little 467, girl 419, oh 417, know 414, get 402, go 383, one 353, can 347, day 345, ain’t 331…
The original image is the cover from one of their latest albums.
Lisbeth gaze
Download (English) millenium-eng.pdf (215kB).
Download (Spanish) millenium-esp.pdf (235kB).
Based in the Stieg Larsson Bestseller. All the words from the Millenium trilogy.
In this case the problem was the huge step between the first words. Take a look at the word list:
blomkvist 2521, salander 2376, police 879, vanger 878, berger 703, zalachenko 589, murder 584, lisbeth 526, investigation 475, apartment 468, harriet 453, bjurman 448, bublanski 405, mikael 396, armansky 379, millennium 356, security 345, coffee 322, martin 319, computer 309, wennerström 307, ekström 302, svensson 300, henrik 288, niedermann 287, spent 286, taken 284, giannini 270, photograph 268, desk 267.
In only 30 words we have tenth of the initial size. The words becomes like ants quickly.
So I decided to insert a kind of ‘brake’ in the algorithm that makes the steps between words shorter. Yes, we lose accurate proportionality but still retain importance degree between words.
Images free for personal use only.
The spanish version uses the spanish books. No google translation.
Let there be House
Download house-eng.pdf (234kB).
Download house-esp.pdf (264kB).
House MD is one of my favorites TV show, I really enjoy the show. House deserves a tribute!.
Hands on it, I collected all the subtitles of the first five seasons from the website http://www.tvsubtitles.net/ something like 115 episodes.
Because the subtitles are ‘common language’ there is not so much information as in a song or a speech. I needed to clean up the word list in order to have a significant result.
So I increased the numbers of words that the algoritm will discard during the counting process
using the 1000 most commonly used English words that I found in http://www.duboislc.org/EducationWatch/First100Words.html
I also realized that there is a lot of strange words with only one hit, probably due to the nature of the subtitles. I decided to include only the words with two or more hits.
Here is the final image!… Cuddy would be proud.
As usual, all files for personal use only.
Goodbye Michael…
Download Michael Jackson (English version).pdf (190kB).
Download Michael Jackson (Spanish version).pdf (188kB).
This is an updated version of my ‘goodbye message’ for Michael Jackson. This time I collected more than four thousand messages that people posted in http://www.lacortedelreydelpop.com/ after the sudden death of Michael.
All the messages were written in Spanish so, in this case, the English version is a direct translation of the spanish using Google.
I did not discrimÃnate. The image contains all the words of all the messages… even the ‘not so nice’ ones.
20 first words:michael 3158, always 2734, music 1509, king 1423, jackson 1173, pop 1164, heart 1158, life 1023, thanks 919, never 870, world 869, peace 820, best 40, god 725, left 723, big 716, dead 664, rests 656, believe 651, alone 648.
My apologies because I cannot find the website that hosted the original image. It was a very nice abstract image of an asian artist…. I think.
Those images are free for non-commercial personal use.