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Eyebrows have been raised at the steady rise in popularity several potentially Vocaloid inspired names have enjoyed in Japan’s baby naming; Ren (ranked 4th), Rin (7th), Kaito (13th) and most notably Miku (up to 24th from 50th last year).

You can see the results below:

(Duplicate names are due to different characters being used)

Girls:

1. Aoi
2. Yui
3. Hina
4. Rin
5. Yua
6. Yuia
7. Miu
8. Sakura
9. Miyu
10. Nanami
11. Misaki
12. Yuuna
13. Yui
14. Mio
15. Miyu
16. Yuuka
17. Kokoa
18. Kanon
19. Riko
20. Miyu
21. Mizuki
22. Yuuna
23. Airi
24. Hinata
25. Miku

Some of these names may look like ita-names, but are probably the other way round. Quite a few characters crop up called “Rin”, so collectively some effect may be possible.

In the case of Miku, it seems an effect is quite plausible as the name has ascended 25 places in one year, nearly doubling, whilst the non-Vocaloid spelling of the name (though it is written in katakana) has remained steady.

Still, it was popular in prior years too… Let us not be hasty.

Boys:

1. Hiroto
2. Ren
3. Yuuto
4. Yuuto
5. Yuuto
6. Shouta (Shota)
7. Yamato
8. Souta
9. Yuuma
10. Sora
11. Haruto
12. Haruto
13. Shou
14. Daiki
15. Yuuta
16. Takumi
17. Yuuta
18. Hinata
19. Kaito
20. Tsubasa
21. Yuuto
22. Yuuki
23. Haruto
24. Rikuto
25. Eita

As usual a fairly boring set of male names, which might benefit from less over usage of -ta and -to. Likely -rou is not included here, because it is a suffix, with the same being true of -ko.

Kaito and Hayate also make appearances further down the list, though otherwise, save “Shota” and Ren, there aren’t a great deal of interesting ita-names.

You are doubtless familiar with strange, and sometime irresponsible names being used more frequently in recent years, with quite a pronounced effect visible in western English speaking areas. We might take the above tables with a grain of salt, but we hear on 2ch of school registers including such delightful names as “Mariririn” and “Miruku” (Milk)…

The original tables (previous year’s ranking is displayed too), from here:

name_txt_b1
name_txt_g1

The usual mass media statistical disclaimers apply: they haven’t disclosed their source/sample as clearly as we might like, though they do have four years of data, and apparently the data covers 40,000 names so it sounds quite reasonable.


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