a picture is worth a thousand words

Visualizations

Mensaje Navidad 2012

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Ya han paso tres años desde que elaboré una visualización relativa a los mensajes de navidad del Rey Juan Carlos y he pensado que sería interesante actualizarlo incluyendo estos últimos años de crisis.

Así que he tomado los 37 mensajes, desde 1975 a 2012, y he analizado las palabras que más ha utilizado para luego representarlas en uno de sus retratos. Como es habitual el tamaño de las palabras tiene una correspondencia con el número de veces que la palabra aparece en los mensajes.

He incluido un gráfico con la evolución de las palabras a lo largo de los años y la combinación de dos palabras representativas. Si lo miráis con detalle podréis apreciar cosas curiosas, como ciertas palabra son sustituidas por otras o que prioridad tiene ciertos conceptos según la etapa política.

Pero como siempre la interpretación os la dejo a vosotros, lo que yo represento son meros datos impersonales!.

Ah, y Feliz Navidad!.

Descargar PDF.


Isaac Asimov

I’m really excited with Curiosity and the fact of be able to explore another world in the search of life. It’s incredible how far we can go and how little is that distance comparing with the size of the whole Universe. It remains me something… if humans can do it why others can’t do the same to us.

And my mind always ends in all those fantastic Isaac Asimov books. He filled my dreams with space travels and incredible adventures, so I think it’s time to do a little tribute.

For this illustration took more than 170 Asimov books, counted all the words and spread over a portrait of the famous writer. Here is the beginning of the word list: robot (26560),human (14363),derec (10679),something (10167),away (8922),without (7549),another (7212),moment (7005),anything (6686),matter (6652),don (6631),felt (6074),dr (6063),law (6039),around (5992),re (5861),quite (5820),smiled (5550),almost (5468),suppose (5399),reason (5383),suddenly (5150),understand (5095),ariel (4964),arm (4915),planet (4829),space (4785),ll (4733),really (4665),stared (4573),case (4571),mr (4567),believe (4560),however (4546),baley (4544),hunter (4542),least (4242),else (4229),maybe (4170),brain (4106),sir (4083),upon (3948),return (3852),remained (3806),seen (3795),control (3772),seldon (3772),speak (3698),computer (3680),nature (3643),nodded (3633),rather (3631),hari (3629),die (3577),daneel (3553),kill (3535),slowly (3524),wall (3506),sense (3494),wrong (3451),hope (3450)…

It’s nice to compare it with another great scifi writer, Stanislaw Lem. I will (someday) create an illustration about him but I have some of the work already done. Following you can see the beginning of the most commonly used words in 20 books of Lem: something (1600),without (1346),around (1178),another (1126),human (1055),fiction (984),wall (978),everything (954),suddenly (948),away (924),doctor (924),existence (889),moment (864),engineer (851),cloud (834),return (830),planet (829),nature (812),case (811),already (800),stefan (797),matter (758),anything (739),gregory (735),arms (722),become (714),space (693),remained (691),later (685),understand (672),felt (670),along (654),someone (652),however (644),inside (644),whether (640),reason (635),almost (619),glass (607),window (604),intelligence (603),control (601),least (598),really (598),believe (597),continued (596),information (594),author (588),system (587),thus (587),result (581),quite (580),taken (565),universe (564),therefore (559),robot (558),structure (558),captain (555)…

Nicely robot is now in 56th position!. Both great but deeply different writers, don’t you think so?.


Rabindranath Tagore

Rabindranath Tagore can deeply touch you. His words can magically wake up something inside you… It’s something like the taste of true.

Very well know by his Music, Art, Theatre, Novels, Stories and Poetry almost all his works focused on religion and racial humiliation related to India. He won the Nobel Prize in Literature in 1913, becoming the first non-European who won it.

The image was composed using words from the Song Gitanjali. I choose using the original language of the song. Love the shapes of the Bengali characters!.


Bruce Lee

And talking of my youth I have to admit I loved Bruce Lee movies. But only recently I discovered the creative side of Bruce Lee. Yes, he was more than a movie actor. Bruce also was film director, screenwriter,  founder of a martial arts movement, philosopher and even wrote poems. He was a creative man with a brilliant mind.

Because of that, and mostly because he filled my childhood with fun and popcorn, I took more relevant people, actors and legendary figures around Chinese martial arts and spread it over a portrait of Bruce Lee.

Below another version of the same illustration.


dIRE sTRAITS

Buf!, more than two months without posting… It’s has been a challenging time with lot of things around my head. I would liked to return with some new things for you (still working in video and other crazy ideas), but I don’t have time enough. So here I go again with a new illustration, I have dozen unfinished just waiting for…something!.

Time to talk about the best band ever: Dire Straits. Yeah I’m getting old but the true is that I never tire listening this band songs. Sultan of Swing, Telegraph Road, Tunnel of Love… too many incredible songs. What can I say… Hey Knopfler THANKS!!!

My first idea was to count the most used words in his lyrics. I took around 50 songs and counted it. The beginning of the list: got (85),come (78),just (76),get (65),like (65),know (64),say (63),now (61),can (54),twisting (42),love (40),go (39),one (39),time (38),baby (37),take (37),away (35),yeah (34),give (33),see (30),way (30),well (30),make (29),pool (28),long (27),night (27),play (26),think (26),never (25),sometimes (25),man (24),around (23),boys (23),day (23)…

But finally I decided to take the songs names. Remove non significant words and randomly sorted the rest of them. Then I moved “Sultans” to the first position as a tribute to Sultans of Swing :-). Also I found the font used in Alchemy cover and change all the words to inverse case so it looks, more or less, like this mythical album cover. Of course Mark Knopfler is the main subject of this illustration.

You can also download free wallpaper in different sizes: 640×480 800×600 1024×768 1152×864 1280×800 1280×1024 1366×768 1440×900 1600×1200 1680×1050 1856×1392 1920×1080 1920×1440 2048×1536

Below you can take a look to some other illustration I finally left behind…


Lovecraft

This days we are commemorating the 75th Howard Phillips Lovecraft death anniversary (is he is really death?) and I think it’s the right moment to do a little tribute to the master of horror.

For this illustration I took the complete works of Lovecraft, from this website, and counted the most used words dropping this list: one (1650),things (1185),old (992),seemed (952),now (892),great (873),time (869),even (831),like (804),night (709),man (691),saw (691),though (675),place (664),must (643),found (602),house (592),came (585),strange (585),might (565),looked (551),whose (540),come (539),certain (533),long (525),upon (518),black (516),dreams (514),never (491),men (490),city (486),dark (484),light (484),made (480),day (477),much (472),thought (464),know (461),still (461),stone (449),years (448),many (446),see (444),beyond (438),two (437),first (434),last (427),well (423),heard (414),world (408),eyes (407),seen (404),fear (401),form (399),far (397),knew (397),sound (397),open (391),yet (388),room (386),street (386),almost (384),back (384),told (382),near (381),way (381),door (378),new (371),walls (371),face (370),horror (369)…

The font used in the first illustration was “Nightmare 5” from dafont.com. For the following I used “Lovecraft’s Diary” font with nice alphabet inspired in Necronomicon (I think).

 


Titanic 100 Years

There are a lot of people talking again about Titanic, and it’s because next April 14 will be the 100th anniversary of the disaster.

It’s amazing to see how people’s fascination with the Titanic is growing day by day. Facts, legends, mysteries, new theories… everything surrounding Titanic generates a powerful attraction.

But remember, 1.500 people died that day. And for most of them it was a travel to hope.

As a tribute to them, and because I can’t escape from Titanic attraction, I spread the names of the 1.500 victims (taken from this website) over a picture and a painting of Titanic.

You can also download vector pdf version:

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Charles Dickens

There is a lot of people celebrating two hundred years of Charles Dickens and I also want to do a little tribute to this great English writer.

I took more than fifty books and novels by Dickens (including the most iconic like Oliver Twist, David Copperfield, Great Expectations, A Tale of Two Cities and A Christmas Carol) and counted the words. I spread the words over two different portraits images.

The first words in the list. oliver (868),upon (755),replied (548),bumble (399),gentleman (366),lady (359),sikes (357),dear (330),jew (325),fagin (317),sir (314),away (298),another (275),without (253),woman (229),poor (204),window (202),shall (192),heart (185),quite (181),child (177),arm (172),brownlow (167),something (166),returned (164),doctor (161),master (161),manner (160),whether (156),moment (153),observed (152),seen (150),london (149),sat (149),indeed (147),present (147),office (145),rather (145),bill (144),speak (143),expression (139)…

The illustrations represents the single word counting, but I also counted two and three words combo. If you are curious the three words combo list start with: gentleman in the white waistcoat (13),poor mercantile jack (11),waiter who ought to wait upon (8),great salt lake (7),queer small boy (7),spoken young man (7),well spoken young (7),french flemish country (6),titbull’s aims houses (6)…

Another portrait.

Did you know that his life is probably most challenging that any of his novel histories. Visit his Wikipedia article to know more about this incredible man.


Madonna

She is more than a singer, probably the smarter and talented artist out there. With more than 300 million records sold worldwide, along 30 years of career, she is probably the most successful woman in the music industry.

I took more than four hundred Madonna lyrics and counted the most commonly used words. Again Love is the most used. The beginning of the list: love, know, get, can, like, just, want, baby, make, time, go, got, feel, one, take, say, never, come, see, now, waiting, oh, give, cause, heart, think, thing, keep… In the above illustration words size is proportional to it’s repetition. As seed image I took the album cover of “True Blue”.

Along the years she changed a lot her music and her image but I still love the more “Like a Virgin” (yes I’m getting old!) and I never tire of “Dress You Up” music video. No special effects, no composition, live… pure Madonna!. That’s the reason why I did this second illustration based on one of the video moments.


11.11.11 happy end of the world

You know, people are crazy about dates and today, in our calendar, we have funny date numbers: 11/11/11. I though most of the people think about it in a negative way, I mean they could become mad because the end of the world or something… So how to check what people think about it?, this time we are going to use Tweeter.

I took around 10.000 English tweets which talks about 111111 and counted the words they used. Surprisingly everyone is having fun with this date. Almost nothing about bad news and a lot of funny things like birthdays, parties, weddings and date facts… smart guys!.

In first illustration I took avatars of all these tweeters and spread them over an image of a render I did with the date numbers (click too see the my original image). In the following I spread the words they used with sizes proportional to it’s repetition. And also you can find two alternative versions.

Seize the day, have fun!.


Debate Rajoy – Rubalcaba

Desde el punto de vista de la visualización de datos los debates políticos son muy interesantes ya que aúnan concisión y espontaneidad, aunque efectivamente esto es muy discutible en muchos casos donde se produce una simple sucesión de monólogos o la mayor parte de los temas están de antemano pactados.

En esta ocasión se enfrentaban  dos de los candidatos a presidente del gobierno en España (aunque no lo crean hay más) en un formato algo más flexible de lo habitual al que creo que merece la pena ‘echar un vistazo’.

Gracias la transcripción de debate publicada en eskup.com podemos analizar las palabras más utilizadas por Rajoy y Rubalcaba.

Rajoy, 1930 palabras utilizadas, las más usadas: hacer (16),porque (13),todos (13),millones (12),economía (10),empleo (10),debe (8),españa (8),españoles (8),gestiona (8),política (8),trabajar (8),desempleo (7),gastar (7),gobierno (7),hablar (7),pensiones (7),pública (7),puede (7),sanidad (7),yo (7),bien (6),eso (6),está (6),estado (6),euros (6),garantizar (6),muchas (6),nuestra (6),país (6),sus (6),tener (6),tiene (6),tres (6),vamos (6),voy (6),cosas (5),entre (5),generamos (5),hemos (5),nosotros (5),paga (5),partidas (5),quieren (5),reforma (5),sirve (5),son (5),cinco (4),competentes (4),congela (4),crear (4),cuando (4),dinero (4),gran (4),haber (4),hecho (4),importa (4),impuesto (4),iva (4),laboral (4),mal (4),materia (4),mundo (4),nadie (4),recortes (4),ser (4),soy (4),sube (4),ya (4)…

Rubalcaba, 2554 palabras utilizadas, las más usadas: hacer (21),pública (17),programa (16),sanidad (14),habla (13),sobre (13),tiene (13),creo (12),dice (12),está (11),trabajadores (11),desempleo (10),eso (10),hemos (10),ley (10),años (9),quiere (9),señor (9),sistema (9),yo (9),cambiar (8),comunidades (8),dos (8),gustaría (8),pasando (8),pensiones (8),seguro (8),solo (8),también (8),bancos (7),diga (7),educación (7),empleo (7),privada (7),todos (7),bajar (6),crisis (6),dinero (6),diputaciones (6),economía (6),españoles (6),están (6),este (6),financiación (6),he (6),hecho (6),lleva (6),muy (6),pregunte (6),problema (6),puede (6),rajoy (6),tenemos (6),ahora (5),ahorro (5),cosa (5),cuando (5),gobierno (5),homosexual (5),mucho (5),ni (5),porque (5),quitar (5),revisar (5),sabe (5),sin (5),aclarado (4),acuerdo (4),algunas (4),cada (4),casas (4),contra (4),debate (4),empresas (4),entre (4),españa (4),europa (4),hombre (4),igual (4),impuesto (4),llegado (4)…

En la ilustración el retrato de cada uno tiene las palabras que ha dicho, cuanto mayor es el tamaño más ha utilizado esa palabra en el debate. Una vez colocadas todas las palabras en su tamaño, y para reproducir lo mejor posible el rostro de cada candidato, se han vuelto a reutilizar las mismas pero ya en el menor tamaño posible.

Las fotos están tomadas de la publicidad electoral.


In Obama’s Words

This is not my first post about Barack Obama. One of my first words illustration was done in 2009 by using all the Obama speeches in the run for president. Nice words for people, I have to say. He became president in January 2009 and the thing got serious.

It has been nearly three years and now we can analyze the words he used in his speeches throughout this time. Nicely people at washingtonpost.com has around 800 Obama speeches ready to be read (also, I have taken the title!) . It was not an easy task because I had to isolate Obama words from all the recorded text, most of them contains words from other people and press questions, etc… I sorted all the speeches because I want to know the word’s evolution in time.

With all these ‘cleaned’ speeches, and using my own tools, I did three different kind of analysis. First I counted the most used words, and also the combo of two and three (significant) words. Also I looked at word’s evolution in time from January 2009 to October 2011.  And finally I looked at the words analyzing distance from others.

Most used single words: going (10817),make (8059),people (7843),can (6912),just (6511),work (6368),know (6165),now (6036),want (6013),get (5620),got (5290),right (5149),years (5148),american (5028),jobs (4789),think (4705),one (4615),time (4520),country (4457),america (4078),states (3879),like (3680),thank (3677),need (3536),help (3491),businesses (3305),things (3275),also (3265),take (3215),way (3199),well (3163),new (3159),sure (3094),say (3064),back (2980),economy (2957),health (2905),come (2898),care (2749),nation (2701),good (2624),united (2565),world (2565),every (2562),everybody (2521),look (2502),families (2469),see (2464),said (2460),tax (2414)…

Two words combo: make sure (2700),united states (2302),health care (1864),right now (1204),small businesses (1143),american people (1122),thank you very much (840),middle class (766),clean energy (739),tax cuts (693),across the country (680),health insurance (645),young people (629),states of america (621),long term (619),two years (516),$ billion (508),god bless (491),want to thank (484),want to make (481),white house (478),around the world (477),move forward (476),insurance companies (475),men and women (462),years ago (457),st century (452),create jobs (450),last year (435),going to make (401),just want (401),private sector (392),can make (367),wall street (366),work hard (366),every day (357),work together (356),one of the things (352),next year (344),recovery act (341),tax breaks (337)…

Three words combo: united states of america (618),want to make sure (302),middle class families (292),health care system (251),health care reform (231),small business owners (227),bless the united states (185),god bless the united (183),health care costs (182),since the great depression (169),got to make sure (166),big round of applause (164),people back to work (150),last two years (144),right here in the united states (138),private sector jobs (128),put people back (124),going to make sure (120),president of the united states (117),investment in clean energy (114),give them a big round (110),cost of health care (106),every single day (106),make sure that we’ve got (106),live within our means (103),can make sure (102),giving tax breaks (97),dependence on foreign oil (96)…

The leading illustration was done by spreading the most commonly used words over a portrait of Barack Obama.

In the next graph you can see the evolution of the first 100 words in time, and the combo of two and three words. Click to enlarge, but if you want to see a high resolution go to this Zoom.it link.

The next group of illustrations represents words close to the main word in all the speeches. So the bigger the word is the more times it appears close to the main word. The distance to the main word is the average distance of all the instances of that word. There is no relationship between each illustration, so you have to look at each one as independent single analysis. Main words sorted alphabetically.

And my word’s trees. The bigger are the most commonly used. You can find the single words tree and the two and three words combo trees. There is a high-res image of the single words tree uploaded at Zoom.it .

 

 

I personally have drawn interesting conclusions about the use of words. But I prefer that each draw their own conclusions. Here there is only data… in a visual way.


Dennis Ritchie

A couple weeks ago Dennis Ritchie pass away. His left was less noisy, just short news in newspapers, but I have to tell you the true: Without Dennis Ritchie there would be no Steve Jobs (of course Jobs was a incredible genius too).

Dennis created the C programming language and, in collaboration with Ken Thompson, the UNIX operating system. Both pilars of our current digital era.

I was tempted to spread one of his best know quotes “C has the power of assembly language and the convenience of… assembly language”, witch is quite funny (if you ever try C!). But finally I took  Ãlvaro from photoblues suggestion and spread all C functions over a portrait of Dennis. I want to thank Ãlvaro for his help with this illustration.

Bye dmr, I hope you see you in comp.lang.c.heaven.


Joaquín Sabina

Joaquín Sabina es uno de los artistas españoles más queridos por el público. A su sencillez le acompañan sin duda las mejores letras de canciones escritas en español.

Buscar esas palabras que hacen la magia en sus canciones me ha llevado a analizar el contenido de 233 de sus canciones (todas, o casi) con los siguientes resultados.

Palabras más usadas: pasado (188),noche (159),quiero (150),llamaba (137),corazón (127),ruido (118),deja (113),besos (109),cantar (109),amor (107),vida (97),pisa (96),sal (95),vivir (95),nunca (92),mar (83),mal (82),olvido (81),siempre (79),canción (70),dijo (69),perder (69),acelerador (68),primer (68),muerte (67),casa (64),decir (64),lleva (64),mira (64),madrid (63),mujer (63),hablo (62),llegar (61),busca (59),dice (58),mano (58),ven (58),fin (57),queda (56),ganas (55),espera (54),quería (54),mejor (53),tarde (53),cama (51),cuento (51),bar (50),buen (50),sueños (50),bien (48),pido (48),corta (47),digo (47),dormir (47),mata (46),mentira (46),nadie (46),negro (46),ojos (46),pon (46),verdad (46),bailar (45),vino (45),volver (45),dame (44),guerra (44),lado (44),mujeres (44),tal (44),veces (44),contar (43),falta (43),niño (43),quiso (43),media (42),muere (42),pongamos (42),toca (42),boca (41),ciudad (41),calle (40),cielo (40),duro (40),pago (40),aprender (39),escribo (39),igual (39),pregunté (39),tren (39),triste (39),viejo (39),loco (38),mientras (38),pan (38),tiempo (38),acaban (37),hombre (37),puerta (37),voy (37),aquel (36),contigo (36)…

Combinaciones de dos palabras: pisa el acelerador (67),sóngoro cosongo (19),hablo de madrid (17),pongamos que hablo (17),and roll (13),oiga doctor (13),rock and (13),mismo fue lo que yo le pregunté (12),pasándolo bien (12),mes de abril (11),noche que yo amo (11),dame tu santa (10),día siguiente (10),escriben las canciones (10),incluso en estos tiempos (10),quién me ha robado (10),rocanrol de los idiotas (10),santa bendición (10),nube negra (9),tablas en el ajedrez (9),vecino de arriba (9),abrigo y ven (8),deja el abrigo (8),noche de bodas (8),robado el mes (8),sitio para los dos (8),veinte años (8)…

Combinaciones de tres palabras: pongamos que hablo de madrid (17),rock and roll (13),dame tu santa bendición (10),deja el abrigo y ven (8),quién me ha robado el mes (8),robado el mes de abril (8),nada va a pasar (7),va a pasar que no queramos (7),bocata con lima te llevaré (6),lado del telón de acero (6),llevaba medias negras (6),nacemos en cualquier lugar (6),pido primer para desertar (6)

La imagen represente un retrato de Sabina con las palabras más utilizadas. Cuanto más las ha usado mayor tamaño tienen en la ilustración.

Otra versión.


iLive

A tribute to Steve Jobs, and incredible man that will iLive forever in our minds.

For this illustration I took more than 2.500 messages people left after his dead. I spread the most commonly used words over a portrait of Jobs. After a couple different tryous I ended with this abstract illustration. This one is my favorite, so I’m going to follow Steve’s advice choosing the one I like the more instead of the (probably) most popular.

Most used single words: steve (1026),jobs (813),apple (475),thank (397),world (359),rip (352),one (346),peace (322),family (248),rest (230),technology (230),like (215),people (215),man (214),great (213),products (212),may (208),innovative (202),genius (194),thing (192),just (191),sad (182),missed (180),time (178),live (172),life (153),changed (150),computer (148),brilliant (147),legacy (147),made (136),never (136),read (136),history (129),forever (127),find (124),know (124),many (123),years (122),good (120),iphone (120),day (119),go (119),can (116),future (115),way (112),now (111),visionary (111),love (110),person (110),invent (107),taken (107),work (107),died (105),team (105),make (104),mr (104),level (103),company (102),god (98),think (98),mac (96),use (96),propel (95),tombstone (95),true (95),much (94),ipad (93),say (92),better (91),come (87),even (87),see (87),cancer (86),get (84),vision (78),always (77),really (77),well (77),lost (76),still (76),truly (76),remember (71),respect (71),first (69),friends (69),best (67),created (67),hope (66),ever (65),american (64),news (64),take (64),human (63),ipod (63),today (63),passing (62),inspiration (60),long (57),death (56),lot (56),bless (55),fan (55),want (54),condolences (53),give (52),done (51)…

Two words comobo: steve jobs (524),rest in peace (183),rip steve (143),one more thing (104),may his family (102),find peace (100),family find (96),jobs and his team (96),forever be our future (95),genius to the level (95),history that have taken (95),legacy will forever (95),level steve (95),propel technology (95),taken genius (95),team did to propel (95),thank you and may (95),tombstone should read (95),thank you steve (85),apple products (83),changed the world (68),sad day (51),god bless (40),condolences to his family (34),peace steve (34),may you rest (33),world a better (32),family and friends (31),rip mr (26),better place (25),thomas edison (24),great man (23),personal computer (23),true visionary (22),world has lost (20),apple fan (19),good apple (19),great innovator (19),thanks for everything (19),apple bites (18),bill gates (18),bites you gave (18),many people (18),one of the greatest (18),steve for the good (18),hard work (15),henry ford (14),hope apple (14),like apple (14),like steve (14),world will miss (14),may god (13),miss you steve (13),mr jobs (13),pancreatic cancer (13),passed away (13),people like (13),sad news (13),changed my life (12),go out to his family (12),just like (12),long time (12),thoughts and prayers (12),american icon (11),apple computer (11),brilliant man (11),changed the way (11)…

Three words: may his family find (96),steve jobs and his team (96),family find peace (95),genius to the level steve (95),history that have taken genius (95),jobs and his team did to propel (95),legacy will forever be our future (95),level steve jobs (95),taken genius to the level (95),team did to propel technology (95),thank you and may his family (95),rip steve jobs (50),rest in peace steve (31),may he rest in peace (30),world a better place (19),apple bites you gave (18),good apple bites (18),thank you steve jobs (18),steve for the good apple (17),thank you steve for the good (17),condolences to his family and friends (13),peace steve jobs (10),changed the world for the better (9),god bless you and your family (9),make the world a better (9),like steve jobs (8),prayers go out to his family (8),may your soul rest (7),steve jobs was one (7),use apple products (7),go into the history books (6),god bless steve (6),graphical user interface (6),rip mr jobs (6),steve jobs will be missed (6)…

You can also use it as wallpaper, choose resolution: 640×480 800×600 1024×768 1152×864 1280×800 1280×1024 1366×768 1440×900 1600×1200 1680×1050 1856×1392 1920×1080 1920×1440 2048×1536

Thank you Steve and Bon Voyage!.


Jim Morrison

Here we go again. This time we will talk about Jim Morrison, singer and lyricist of The Doors. He is one of the most iconic men in the rock history, but I want to point you to his poet side. Did you know Morrison improvised poetry while the band was playing live?.

Again I counted the words of all of their lyrics and spread over a well know portrait of Morrison. Bigger is more used. The beggining of the word list and it’s hits: love (96),yeah (61),tell (56),run (51),girl (47),see (47),come (44),know (44),time (43),baby (41),night (41),get (39),back (38),like (37),one (37),please (37),now (36),end (35),little (35),blue (34),people (30),can (27),make (27),waiting (27),change (26),children (25),oh (25),streets (25),town (25),way (25),got (24),live (24),look (24),sun (24),eyes (23),risin’ (23),go (22),right (22),well (22),woman (22),c’mon (21),good (21),man (21),take (21),free (20),moon (20),blood (19),follow (19),friend (19),l’america (19),must (19),ride (19),want (19),break (18),city (18),dead (18),gone (18),lies (18),listen (18),need (18),soon (18),strange (18),world (18),snake (17),summer (17)…

And again “love” is the first one.

He used it only in six songs, but “little girl” is the most commonly used two words combo, with 16 hits.

You can also download a wallpaper version for the following resolutions: 640×480 800×600 1024×768 1152×864 1280×800 1280×1024 1366×768 1440×900 1600×1200 1680×1050 1856×1392 1920×1080 1920×1440 2048×1536

This is the end Jim… Wild soul we will miss forever.


Palabra de Zapatero

Después de casi 8 años de gobierno es hora de saber que nos ha venido diciendo Zapatero durante todo este tiempo.

Realmente la política no es algo que me guste, pero sin embargo es una fuente inagotable de información ‘cuidadosamente diseñada’ a la que creo interesante poder ver desde un ángulo diferente.

Así que he analizado 1.152 intervenciones de José Luis Rodríguez Zapatero. Las he tomado de la mejor fuente posible, la web oficial de La Moncloa, las he ordenado cronológicamente y he dejado exclusivamente las palabras que ha dicho el propio Zapatero, eliminado cualquier otra intervención. Dicho de una manera más simple, solo analizo lo que ha salido de su boca.

Entre estas intervenciones se encuentran discursos, entrevistas, declaraciones, conferencias de prensa e intervenciones parlamentarias.  Un batiburrillo que quizás merezca  la pena disgregar en el futuro, ya que no es lo mismo una respuesta a un periodista que un discurso preparado con tiempo (obviamente este último es mucho más interesante).

Para el análisis primero he realizado un cómputo real de las palabras con ayuda de un lematizador (que permite sumar palabras basándose en su raíz, por ejemplo: país=países, económica=económicos, etc…). En este proceso se descartan las palabras que no tiene valor significativo, como por ejemplo: el, la, por, etc… Con los datos obtenidos he reconstruido las distintas visualizaciones, siempre utilizando herramientas propias que supongo ya habéis visto por esta web.

Visualizaciones basadas en Retrato. El algoritmo reconstruye el rostro de Zapatero utilizando las palabras con tamaños proporcionales a las veces que se repiten. De esta manera las que aparecen más grandes son las más utilizadas en las intervenciones. Esta versión difiere ligeramente la de la cabecera del post.

Evolución de las palabras cronológicamente a lo largo de los años de gobierno. Se analizan palabras individuales y combinaciones de dos y tres palabras significativas. Aquí se puede ver cuando la utilización de la palabra ‘crisis’ empieza a ser significativa o como ciertas combinaciones nacen y mueren repentinamente, por ejemplo ‘sistema financiero internacional’. Ojo, el archivo es de gran tamaño, es mejor descargarlo desde “Guardar enlace como…” o también puedes verla desde este enlace en Zoom.it.

En las siguientes visualizaciones se analizan solo las palabras más cercanas a una palabra objetivo y se representan como una nube. El tamaño de las palabras es proporcional al número de veces que se repite la misma y la distancia al centro es la media de las distancias a dicha palabra de todas las instancias encontradas. ¿Quién diría que la palabra que más aparece junto a ‘familia’ es ‘política’?.

Por último un par de visualizaciones basadas en árboles. Estos se reconstruyen utilizando las palabras con un tamaño proporcional a las veces que se ha utilizado en las intervenciones. Las más utilizadas son las que se colocan primero formando la base del árbol. La forma del árbol es básicamente aleatoria.


Just one more thing…

Peter Falk, the unforgettable Lieutenant Columbo, left us last June… No more heros with battered raincoat. As a tribute (and probably because I want to be part of Columbo, in some way…) I collected around 1.000 reactions people left (in huffingtonpost.com and eonline.com) after his dead, and recreated his portrait with the most commonly used words.

Do you know that Columbo’s scriptwriters, William Link and Richard Lewison, admitted they based most of the character of Lieutenant Columbo on Falk himself?.

The beginning of the single word list: falk (471), columbo (398), one (389), peter (338), great (297), rip (293),loved (256), actor (213), missed (212)…

If we count three words combo: just one more thing (71), rip peter falk (23), loved peter falk (18),one of my all time favorite (16)…

Wait Peter!, don’t leave!… just one more thing…


U2 by colours

I really think U2 is more than a band… They aren’t just musician, since 1980s the Irish group have worked to address issues concerning social injustice.

For this illustration I took more than two hundred lyrics from the band website http://www.u2.com/ and counted all the words. Then I spread all the words over a portrait of Bono. I want to make a little tribute to his various charity and philanthropic campaigns by using the colours of the peace flag randomly in the letters.

The font is one of the most commonly used their cover artworks.

Again “love” in the most used word by far. Take a look at the beginning of the list: love (526),oh (262),like (239),know (236),go (219),come (214),day (174),can (173),see (170),one (149),need (139),want (132),feel (131),heart (129),away (121),get (119),got (117),say (113),walk (112),now (109),take (108),night (107),time (106),man (105),give (96),run (90),back (89),baby (87),make (87),yeah (86),just (82),way (82),look (81),sky (80),thing (78),fall (74),tonight (69),still (68),believe (66),boy (66),light (66),eyes (65),sing (65),sun (63),song (62),turn (62),world (62),girl (61),new (59),around (58),high (58),find (56),hold (56),blue (54),long (51),tell (51),place (50),shadows (50),call (49),face (46),head (46),waiting (46),heartbreak (45),rain (45),room (45),ain’t (44),name (44),shake (44),soul (44),try (44),talk (43),black (42),never (42),nothing (42),god (41),gun (41),happiness (41),last (41),star (41)…

Download PDF: JO-D-110901-Bono01

You can also choose wallpaper resolution: 640×480 800×600 1024×768 1152×864 1280×800 1280×1024 1366×768 1440×900 1600×1200 1680×1050 1856×1392 1920×1080 1920×1440 2048×1536

Another illustration with horizontal text.

Download PDF: JO-D-110901-Bono02


Words for Amy

It was a sad lost of a talented yougn woman. For this illustration I took more than 4.000 comments people left after dead of Amy Winehouse in huffingtonpost.com.

Donwload vector base pdf file: JO-D-110816-Amy01

Also here you have the wallpaper files, in different resolutions: 640×480 800×600 1024×768 1152×864 1280×800 1280×1024 1366×768 1440×900 1600×1200 1680×1050 1856×1392 1920×1080 1920×1440 2048×1536

Most commonly used words: sad (1047),amy (986),talent (804),drugs (706),addiction (624),one (515),peace (498),just (473),people (469),rip (461),life (450),like (380),family (376),hope (337),music (332),now (330),loved (325),can (320),died (317),many (312),know (300),time (296),rest (288),get (284),winehouse (279),young (277),go (272),surprised (260),live (253),think (247),death (243),really (242),much (239),great (237),make (235),way (227),friends (222),say (219),years (219),see (217),may (215),voice (205),never (199),soul (197),coming (194),help (193),waste (193),find (181),another (175),tragic (173),person (170),rehab (168),someone (167),good (166),take (166),well (165),sorry (162),feel (160),try (159),want (154),even (150),fans (150),joplin (147),still (147),alcohol (146),always (145),back (144),said (142),happen (141),shame (140),thing (139),missed (138),artist (135),bad (133)…

If you want the most used two (relevant) words combo: rest in peace (227),rip amy (204),amy winehouse (170),find peace (82),janis joplin (81),family and friends (74),drug addiction (71),great talent (70),jim morrison (61),peace amy (53),kurt cobain (52),peace now (48),jimi hendrix (46),drugs and alcohol (43),may she rest (43),loved ones (40),back to black (37),young woman (37),waste of talent (36),go to rehab (35),years ago (35),god bless (33),died at age (30),drug use (30),many people (30),much talent (30),brian jones (29),found peace (28),long time (28),may you find (27),saw this coming (27),see this coming (27),die young (26),family member (26),loved her music (26),sad news (26),hope she finds (25),incredible talent (25),well said (25),get help (24)…

Also counting three words: may she rest in peace (42),rest in peace amy (42),may you find peace (23),hope she finds the peace (18),make me go to rehab (17),rip amy winehouse (17),tried to make me go (15),talented young woman (14),heart goes out to her family (13),love is a losing game (13),finally find the peace (12),just a matter of time (12),hope she has found peace (11),hope she is at peace now (11),drug and alcohol addiction (10),finally found peace (9),find peace now (9),now amy winehouse (9),go to rehab but she said (8),may her soul rest (8),rest in peace now (8),waste of a great talent (8),alcohol and drug addiction (7),drug and alcohol abuse (7),family and loved ones (7),hit rock bottom (7),hope she has finally found (7),hope she is finally at peace (7),may god bless (7),musicians dying at age (7),another great talent (6)…

Another version of the same illustration.

Download pdf: JO-D-110816-Amy02

One more.

Download pdf: JO-D-110816-Amy03

Goodbye Amy!


Words that kill

Agatha Christie is probably the best crime writer ever. She wrote more than ninety books, but only 82 as Agatha Christie. For this illustration I counted the words of 65 of those books. Including her most famous like “Ten Little Niggers” and “Murder on the Orient Express”. She also have a long list of movie and television adaptations. Take a look at her wikipedia article.

She used the word “murder” only 4158 times… not too bad!.

Most commonly used words: poirot (13236), mrs (10845), mr (9100), quite (7388), something (6469), really (6288), sir (5243), rather (4883), woman (4431), anything (4394), doctor (4167), murder (4158), suppose (3856), away (3611), inspector (3531), marple (3390), lady (3273), moment (3261), believe (3210), dear (2729), suddenly (2719), case (2704), tuppence (2609), matter (2549), smiled (2523), killed (2421), shall (2373), someone (2367), seen (2336), understand (2302), death (2240), wife (2201), nice (2150), dead (2107), felt (2042), died (2036), tommy (2005), nodded (1985), another (1964), police (1940), sort (1927), everything (1917), husband (1902), shook (1897), married (1896), bit (1881), natural (1855), else (1849), oliver (1823), exactly (1822)…

The battle between Hercule Poirot and Miss Marple has a clear winner. Poirot has more than quad hits than Miss Marple.

I’m working in a new implementation of my word-counting tool. The target is to be able to count words combo, instead of single words. I will publish someday a whole analysis, but I want to share some of my first results with you. For these 65 books one of the most used four (representative) words combo are “miss marple shook her head”. And the three words combo winner is “said miss marple” with 1217 hits.

Another illustration. This time the words sizes are proportional to it’s repetition.


Lost, the words they said

This visualization represents the words used by each character of the popular tv show Lost. The size of the words are proportional to the number of times the character used it. The word position and the distance to the character are mostly random.

I don’t like remakes. I prefer to waste my time in new ideas. But I’m going to do an exception with this post. First because when I did it, the show wasn’t end so It was unfinished… somehow. And second because I think that Lost deserve it. I know Lost end received a lot of critiques (I share some of them) but I really enjoyed all the time I spend watching Jack, Ben and Locke making the rounds.

In addition to adding the final season information, I have taken the opportunity to improve the visualization. Remember I know the words each character said, exactly, thanks to the scripts hosted in lostpedia.wikia.com.

Yo can take a look at my original post talking about this image and others here.

Click in the image to see a high resolution version of the visualization. But if you want to see it in his full glory go to this link in Zoom.it.


Words Grow

What if words could grow as trees?. A while ago I did a visualization with the words of all Obama speeches, growing as a tree. I’ve updated my code and tested it with some of the words image I’ve published along the time.

Here you have my huge collection of words trees. The first one represents the Darwin book “On the Origin of Species”.

All these trees have a post reference and represent the most used words of a book, a speech or lyrics. The size of the words are proportional to the number of times the word appears in these books or speeches.

Think on it as a step after the word image creation. Because the words colours of these trees was taken from the colours these words have in the image composition. it’s like a combination between the original words analysis and the image colours.

All the images comes from vector based pdfs.

The most commonly used words of all Lorca poems.

The most commonly used words of all ACDC lyrics.

The most commonly used words of The Bible (New Testament).

The most commonly used words of The Bible (Old Testament).

The most commonly used words of all Bob Dylan Lyrics/a>.

The most commonly used words of all Bruce Springsteen lyrics.

The most commonly used words of the Che Guevara book “Diarios de Motocicleta”.

The most commonly used words of all Miguel Delibes books.

The most commonly used words of messages to Dennis Hopper.

The most commonly used words of all Iron Maiden lyrics.

The most commonly used words of all Gilmore’s Girls shows.

The most commonly used words of all House MD shows.

The most commonly used words of all reactions to the Sara and Iker kiss.

The most commonly used words of words from Jesus.

The most commonly used words of all Juan Carlos speeches.

The most commonly used words of all Nirvana lyrics.

The most commonly used words of all reactions after the dead of Leslie Nielsen.

The most commonly used words of John Maeda book “Laws of Simplicity”.

The most commonly used words of all Marillion lyrics.

The most commonly used words of all Queen lyrics.

The most commonly used words of all messages to Michael Jackson after his dead.

The most commonly used words of all Radio Head lyrics.

The most commonly used words of all Rollig Stones lyrics.

The most commonly used words of all TED talks speeches.


Lorca’s poems

Federico García Lorca has wide range of types of works, but I like a lot his poems, like “A poet in New York”. There is a lot artworks related to Lorca’s works, most of them really beautiful. Probably because it’s inspirational wonderful works.

For this illustration I took all the Lorca poems (in spanish) and counted the most commonly used words.

A nice list, I have to say: niños (215), muerte (210), amor (199), agua (194), corazón (193), noche (180), cielo (156), canto (146), blanco (136), estrellas (130), oh (130), rosa (128), ojos (126), ay (118), luz (118), quiero (117), sangre (117), viento (116), mar (111), mira (111), verde (111), aire (105), negros (105), granada (100)… and another 4.200 different words.

The bigger are the most commonly used.

Another illustration with horizontal text.