Billboard Year-End Top Pop Artists 2004-2007

I took Billboard's Year-End Top Pop artists since 2004: Usher, 50 Cent, Chris Brown and Akon.



Google Insights for Search showed that the artists that "won" earlier also scored higher overall. It bore witness to the staying power of the top stars, I guess. As expected, the year that an artist was declared top artist was usually his top year of Google-popularity. Only Chris Brown peaked much higher later than in his "winning" year.

Weekdays in the UK, Germany, France, Italy, Spain and The Netherlands

Today I faced off the five weekdays in five European countries. Let's start with the UK:



Friday was on top, with an annual peak around Good Friday (typically in March or April). The less-represented Tuesday nevertheless also displayed an annual peak around Fat Friday (Mardi Gras) in February. Monday had a lone but impressive peak in May 2006: I have no clue why. Googlers in the UK were least interested in Thursday. Next, Germany, using the local names (as in all countries; but always in chronological order on the graph, to make comparisons easier).



The ranking in popularity of the weekdays is similar to the UK. No. 1, Freitag, showed a more even trend line though, no real peak for Good Friday. Mittwoch, however, had many serious peaks without a clear annual pattern emerging. Dienstag was dead last. The French days of the week faced off as follows:



They were pretty much all on the same base level though lundi especially had quite a few strong peaks, usually about in May. I suppose the May 2005 one could be related to referendum on the proposed new European constitution (Monday May 30). Mercredi was the overall loser. Now I went down southeast for the Italian stage of our little "Tour of Europe":



I included the unaccented variants of the days in the comparison as Google distinguishes them to a certain extent. The weekdays were more or less bundled together except for uneven trend lines for venerdì, martedì and lunedì especially. The reasons escape me. At the bottom we found mercoledì again. Then it was on to Spain:



This country had a profile unlike any of the others: all days were on similar flat, low levels of interest except for a humongous peak for jueves in July 2007. Again, I am at a loss to explain this anomaly. The least interesting day in Spain seemed to be miércoles but not by a meaningful margin. Finally, we looked into The Netherlands:



Vrijdag won this one. I venture that this is related to Good Friday again: look at the annual peaks. There was even a corollary annual donderdag small peak: Maundy Thursday (Witte Donderdag) perhaps? In Holland, dinsdag was the least interesting.

Golden Retriever vs. German Shepherd vs. Yorkshire Terrier vs. Labrador Retriever vs. Staffordshire Bull Terrier

Using data from the American Kennel Club (2007), the Australian National Kennel Council (2007), the Canadian Kennel Club (2007) and the UK Kennel Club (2006) (see Wikipedia), I calculated what were the five most commonly registered dog breeds in these four countries together: an Anglo-Saxon top 5 so to speak. I did this by assigning ranking points in reverse of the rankings, e.g, the German Shepherd, no. 3 in Canada, got 8 ranking points from Canada. The four kennel clubs' top 10s actually accounted for only 22 distinct dog breeds. This was the full list by the way:

• 1. Labrador Retriever 40
  
• 2. German Shepherd (Dog) 32
  
• 3. Golden Retriever 26
  
• 4. Staffordshire Bull Terrier 14
  
• 4. Yorkshire Terrier 14
  
• 6. Cavalier King Charles Spaniel 12
  
• 6. (English) Cocker Spaniel 12
  
• 8. Boxer 10
  
• 8. Poodle 10
  
• 10. (English) Springer Spaniel 8
  
• 11. Beagle 6
  
• 11. Shetland Sheepdog 6
  
• 13. Border Collie 5
  
• 14. Dachshund 4
  
• 14. Miniature Schnauzer 4
  
• 14. Pug 4
  
• 14. Shih Tzu 4
  
• 18. West Highland White Terrier 3
  
• 19. Dalmatian 2
  
• 20. Bernese Mountain Dog 1
  
• 20. Border Terrier 1
  
• 20. Bulldog 1
  
• 20. Rottweiler 1
  

So what did Google Insights for Search teach me?



Google-popularity ranked the doggies this way:

1. Golden Retriever
   
2. German Shepherd
   
3. Yorkshire Terrier
   
4. Labrador Retriever
   
5. Staffordshire Bull Terrier

This latter list is different from the four-kennel-club rankings. The Labrador Retriever (no. 1) switched places with the Golden Retriever (no. 4). The Yorkie threatened for some time to overtake the German Shepherd but in the end didn't succeed. The Golden Retriever suffered an outspoken decline but stayed clearly on top. But let's look at another feature of Google Insights for Search: split-ups of how the different dogs did in specific countries, starting with the Golden Retriever:



Golden Retrievers were most popular in the US, Austria and Canada. When digging deeper, in the US, the top states were Maine, Colorado and Alaska. How about the German Shepherd?



This time, the US, Australia and South Africa were tops while inside the US it was Alaska, North Carolina and Virginia. Germany wasn't even in the top 10 but of course they would use the German word, Deutscher Schäferhund, to search. Next, the Yorkie.



Lo and behold, Hungary searched most for the lapdog, then South Africa and the US (top states: Georgia, West Virginia, Mississipi). Let's check on the good old Lab:



Labrador Retrievers were Google-popular in the US, the Philippines and Canada. The top 3 US states were Maine, Vermont and New Hampshire. Last but not least, to utilize a well-worn cliché, came the Staffordshire Bull Terrier, a breed with which I must admit I wasn't familiar.



The UK, Norway and Australia were most interested. The US came in only 9th this time (top states: Alaska, Hawaii, Louisiana).

John McCain vs. Barack Obama vs. Bob Schieffer

The third and last US presidential debate took place tonight at Hofstra University in Hempstead, NY. I started by following the same methodology as with the first and second debates and the vice presidential debate, amended regarding Wordle by my 10-5-08 post. So let's start with the bubble graph displaying length of words, sentences as well as number of words:



As usual, the moderator (Schieffer) spoke far less. Obama tended to use longer sentences. I did an extra analysis again, this time focusing on speaking turns and the number of words and sentences per turn:



McCain had the most speaking turns, followed closely by Schieffer. Obama clearly had the least. However, Obama used a lot more words per turn than McCain. Schieffer came in dead last as a moderator should. It seems to me that this pattern was the result of McCain interrupting Obama a lot and Schieffer attempting to stop this. In other words, McCain was more aggressive, pushy.

Next, the by now traditional word clouds.

John McCain





Barack Obama





Bob Schieffer



OK, now what did it all mean? McCain was talking most about Obama—hey, he did call him "Sen." at least—followed by America, and the trio of need, going and now. He did not once use his opponent's first name, Barack: he didn't want to portray him too much as a human being, I suppose? Obama on the other hand used John 8 times, often by itself. Otherwise, his biggest words were going and think. People, now and make came next. Only then do we get down to McCain, health and want. Obama was talking more to the voters, explaining policy. Finally, Schieffer used, of course, Sen. the most but it was more accompanied by McCain than Obama. This reinforced our impression that he was trying to reign McCain in a bit. One more funny thing: Schieffer's catch phrase is "all right": he used it 17 times hence the prominence of right in his word cloud (all is a common word that is filtered out by Wordle).

7-Day Top Searches in Germany, Brazil, the US, Australia and Japan

Using Google Insights for Search's Download as CSV feature, I made a spreadsheet of the top searches for the last 7 days in five countries. For reasons that are unclear to me, the data yielded the top 50 for Germany, Brazil and Australia but only the top 44 for the US and Japan. I established a list of all the unique search terms and made a stacked graph using the standardized values for each country. It's a little big as there's a very long tail, in other words, there isn't a lot of overlap.



I realize the graph is hard to read but Blogger somehow reduced the size. Here are the search terms with their respective total values:

1. youtube 375
   
2. yahoo 290
   
3. google 230
   
4. ebay 180
   
5. myspace 175
   
6. facebook 165
   
7. hotmail 130
   
8. msn 125
   
9. you tube 115
   
10. orkut 100
    
11. jogos 100
    
12. games 100
    
13. wikipedia 90
    
14. maps 70
    
15. gmail 60
    
16. my 55
    
17. craigslist 55
    
18. gmx 50
    
19. amazon 50
    
20. weather 45
    
21. mixi 45
    
22. dictionary 45
    
23. wetter 40
    
24. web 40
    
25. news 40
    
26. 2ch 40
    
27. 価格 40
    
28. test 35
    
29. 楽天 35
    
30. 地図 35
    
31. white pages 30
    
32. web.de 30
    
33. uol 30
    
34. telefonbuch 30
    
35. spiele 30
    
36. real estate 30
    
37. globo 30
    
38. bild 30
    
39. ニコニコ 30
    
40. yahoo mail 25
    
41. tradutor 25
    
42. terra 25
    
43. studivz 25
    
44. mapquest 25
    
45. cnn 25
    
46. baixaki 25
    
47. 天気 25
    
48. westpac 20
    
49. wer kennt wen 20
    
50. tv guide 20
    
51. schülervz 20
    
52. routenplaner 20
    
53. qantas 20
    
54. mobile 20
    
55. leo 20
    
56. hotmail.com 20
    
57. frases 20
    
58. 譬ｪ萓｡ 20
    
59. bebo 20
    
60. anz 20
    
61. ヤフー 20
    
62. yellow pages 15
    
63. yahoo.com 15
    
64. wkw 15
    
65. where is 15
    
66. walmart 15
    
67. vivo 15
    
68. utube 15
    
69. tre 15
    
70. telstra 15
    
71. target 15
    
72. spiegel 15
    
73. seek 15
    
74. red tube 15
    
75. optus 15
    
76. oi 15
    
77. nhk 15
    
78. nab 15
    
79. mensagens 15
    
80. icq 15
    
81. hi5 15
    
82. goo 15
    
83. freenet 15
    
84. firefox 15
    
85. espn 15
    
86. detran 15
    
87. db 15
    
88. commonwealth bank 15
    
89. claro 15
    
90. caixa 15
    
91. big day out 15
    
92. bank of america 15
    
93. asx 15
    
94. aol 15
    
95. 鄙ｻ險ｳ 15
    
96. 螟ｩ豌嶺ｺ亥 ｱ 15
    
97. ノーベル賞 15
    
98. vagalume 10
    
99. tse 10
    
100. trading post 10
     
101. t-online 10
     
102. the age 10
     
103. tchibo 10
     
104. runescape 10
     
105. receita federal 10
     
106. postbank 10
     
107. otto 10
     
108. o2 10
     
109. ninemsn 10
     
110. netbank 10
     
111. net 10
     
112. myspace.com 10
     
113. myspace layouts 10
     
114. msnbc 10
     
115. miniclip 10
     
116. mercado livre 10
     
117. meinvz 10
     
118. jogos online 10
     
119. jogos de meninas 10
     
120. jetstar 10
     
121. jappy 10
     
122. jal 10
     
123. ig 10
     
124. hoyts 10
     
125. home depot 10
     
126. herald sun 10
     
127. google maps 10
     
128. gmx.de 10
     
129. 驛ｵ萓ｿ逡ｪ蜿ｷ 10
     
130. dmm 10
     
131. dicionario 10
     
132. deutsche bank 10
     
133. dax 10
     
134. das Örtliche 10
     
135. currency converter 10
     
136. concursos 10
     
137. club penguin 10
     
138. bom 10
     
139. bol 10
     
140. bigpond 10
     
141. bate papo 10
     
142. barack obama 10
     
143. börse 10
     
144. au 10
     
145. aol.com 10
     
146. ana 10
     
147. americanas 10
     
148. afl 10
     
149. 大和生命 10
     
150. 繝九さ繝九さ蜍慕判 10
     
151. youtube.com 5
     
152. you tube.com 5
     
153. xnxx 5
     
154. webkinz 5
     
155. tv programm 5
     
156. tim 5
     
157. southwest airlines 5
     
158. schuelervz 5
     
159. photobucket 5
     
160. pandora 5
     
161. oi torpedo 5
     
162. nikoniko 5
     
163. my space 5
     
164. msn.com 5
     
165. messenger 5
     
166. letras de musicas 5
     
167. kboing 5
     
168. jra 5
     
169. itau 5
     
170. horoscopo 5
     
171. gyao 5
     
172. google.com 5
     
173. globo.com 5
     
174. g1 5
     
175. fernsehprogramm 5
     
176. facebook login 5
     
177. 貍ｫ逕ｻ鬢ｨ 5
     
178. deutsche bahn 5
     
179. cpz 5
     
180. cifras 5
     
181. caixa economica 5
     
182. bradesco 5
     
183. 遏ｳ逕ｰ譛ｪ譚･ 5
     
184. 邱呈婿諡ｳ 5
     
185. 菴仙ｷ晄\･萓ｿ 5
     
186. 荳画ｵｦ蜥檎ｾｩ 5
     
187. ユーチューブ 5
     
188. 繝ｦ繝九け繝ｭ 5
     
189. 繧｢繧ｲ繧ｵ繧ｲ 5
     
190. 繧ｬ繝ｳ繝\繝  00 5
     

The social networking sites, search, Wikipedia, ... the usual suspects are internationally Google-popular. I must admit I'm a little baffled by the number of people searching for "Google" in the Google search engine: maybe these came from in-browser search boxes? Yahoo mail and weather were only searched in the US. Only Australians typed in games a lot. There are more examples of interesting/puzzling details. Temporarily, the full-scale graph can be viewed here.

B. Geldof vs. Bono vs. FAO vs. Greenpeace vs. H. Kohl vs. Hu J. vs. HRW vs. I. Betancourt vs. K. Kelly vs. M. Ahtisaari vs. M. Tsvangirai vs. Others

Finnish former prime minister and international conflict mediator Martti Ahtisaari has won this year's Nobel Peace Prize. Congratulations! Using Google Insights for Search, I traced the popularity of the most commonly rumored nominees for this prestigious prize during the last 12 months. I experimented with a new format. I downloaded the real, unstandardized number sequences for a large number of nominees and then selected out the 16 with the highest average score. These were then represented as colored bands in a normalized, stacked area diagram:



Notice that Ahtisaari was not exactly the most popular. That role was assigned to rock band U2's musician and activist Bono. Next came Human Rights Watch (HRW), the UN Food and Agriculture Organization (FAO) and Greenpeace. The only other rumored nominee with decent Google-popularity was peace activist Kathy Kelly.