Korean pop culture, in numbers

stars

JAY B of GOT7 is a Thai star, Tempest is a Vietnamese one, and Kim Jong-kook belongs to nobody

Of 214 Korean stars with an article on all four Southeast Asian Wikipedias, 86.6% of the reading about JAY B sits in Thailand alone. An evenly read star would score 25%. Kim Jong-kook of Turbo scores 27.5%.

Southeast Asia does not read about the same Korean stars. It reads about different ones, and the split is sharper than we expected.

Take JAY B of GOT7. Across the Indonesian, Vietnamese, Thai and Malay Wikipedias, 86.6 per cent of all the reading about him happens on the Thai edition alone. Tempest sits at 86.1 per cent in Vietnam. A star read evenly by all four countries would score 25 per cent.

Each country’s own names

We can compare 214 Korean stars — those with an article on all four editions and enough reading to be worth a share. Here is where the concentration lands.

Country Stars concentrated there The most concentrated
Thailand 101 JAY B of GOT7, 86.6%
Vietnam 66 Tempest, 86.1%
Indonesia 39 Gong Myung of 5urprise, 54.4%
Malaysia 8 SISTAR, 57.6%

Thailand’s list runs on: Jinyoung of GOT7 at 60.7 per cent, Kai of EXO at 57.8, Hwasa at 56.2. Vietnam’s has Jung Il-woo at 68 per cent and Park Ji-yeon of T-ara at 67.9. Indonesia’s ceiling is lower — Gong Myung of 5urprise at 54.4, Kim Min-kyu at 54.2, Kim Min-gyu of Seventeen at 49.

Malaysia has eight. That is the finding, not a gap: every star in this table was measured on all four editions, so Malaysia had the same chance to appear as anyone else. A Korean star whose reading concentrates somewhere tends to concentrate in Thailand or Vietnam.

And the ones who belong to nobody

At the other end are the names nobody owns. Kim Jong-kook of Turbo is read at 27.5 per cent in his largest country — two and a half points off a perfectly even reader. Goo Hara of Kara is at 27.9, Lee Hyori at 28.3, Stray Kids at 29.9.

These are the stars whose readership looks the same wherever you stand. There are far fewer of them than there are concentrated ones.

What we did not do

We did not fill a missing article with a zero. A star only enters this table if all four editions have an article about them, because a zero would turn “we cannot see it” into “that country is not interested”, and those are different statements.

We did not use thin numbers. A star needs a four-edition total of at least 20 reads per million to appear, because below that a few hundred views in one country produces a share of 80 per cent that says more about the size of the number than about the country. That floor is ours, and a different floor would move which names appear.

And we caught ourselves counting two people twice. Wikidata carries Gong Myung and Gong Myoung as separate items, and Jinyoung and Park Jin-young likewise. Both pairs showed up as separate rows in the first draft. Rows with identical figures on all four editions are now merged.

What a high share is not

It is not a preference. We measured where the reading sits, not where the liking sits. The four editions serve different numbers of readers with different habits, and scaling by edition size only removes the first of those.

It is not an explanation either. A Thai concentration might be touring, a drama that aired there, a local partner, or something we have not measured. We can say the reading is concentrated. We cannot say why, and we are not going to guess.

The four country lists, the even-reader table and the workings are on whose star is whose.

Where these numbers come from

Sources

What we checked

  • Every star used has an article on all four editions, so no missing article is ever counted as a zero.
  • Rows with identical figures across all four editions are merged: Wikidata carries some people twice under different spellings, and two of them appeared in the first draft of this table.
  • Group memberships were read from Wikidata's member-of property rather than written from memory.

The data behind this

Written from the same data

If you work in this business

Everything on this page is measured from the same weekly Netflix lists, per market and per title. We publish the pages free; what we sell is the same measurement cut to one company's catalogue — including the figures behind /own-star.

What a company sheet contains, and what it cannot tell you →

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