aaronjbecker

interactive data toy to compare state and regional baby name popularity

the measurably whitest names according to the 2020 US Census

you can change start year, %male/female threshold, # names, and also view results combined by pronunciation (e.g. Jordan + Jordyn etc.)

algorithmically grouped, vote on pronunciations here: https://nameplay.org/tools/refinement/Kayden

Grouped by pronunciation. Each of these 152 spellings was given to at least 5 baby girls in a single year. Makayla is actually the most popular spelling overall.

Written about a year ago-- but I've seen both D2 and Mermaid on HN today so I figured I'd share.

Yeah there are a few names that become "unisex" only in the aggregate, with differently gendered usage across cultures-- Alexis is another I can think of, it's a girls' name in the US but a boys' name in most other countries.

I have a follow-up post that covers "common" unisex names, which I arbitrarily defined as names with at least 25k births for both sexes. This one does have more of the names you were probably expecting to see: https://nameplay.org/blog/common-unisex-names-by-gender-rati...

The ranking for the linked post is based on a diversity index, which scores most highly for names closest to an exact 50-50 split. Hence framing it as the "most non-binary" of the unisex names. Admittedly this is more a statistical curiosity than a reflection of everyday life.

I have been working on an algorithm to combine names with pronunciations that overlap, based on ARPAbet phoneme representations from CMU dict + generated by LLMs. The data is still messy, because "creative" spellings are hard for LLMs to deal with: token overlap with primary names is frequently low, and spelling variations only exist because English has such a lax approach to phonics to begin with.

Here's Ryan with its spelling variations: https://nameplay.org/names/combined/popularity/Ryan

the data is not only US specific but also focuses on recent naming trends, with the first chart covering 2000-2024. In the US, Ashley has been overwhelmingly female since the late 1960s: https://nameplay.org/names/combined/popularity/Ashley#gender...

Can an LLM speculate on name origins using the same kind of "when and where" data a human expert might use? Here's my attempt to find out.

Or does this quest to produce less-sloppy name meaning content just add to the mountain of slop already on the internet...?

Interactive directory with links to the inferred origins, for your reviewing entertainment: https://nameplay.org/list/names-with-inferred-origins