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The numbers

Everything on this site that is a number comes from a file. These are the files, added up.

  • 104,819

    Human names on file

  • 372,009,150

    Babies, 1880 to 2024

  • 145

    Years of data

  • 31,904

    Names given in 2024

  • 4,362

    Given to exactly five in 2024

  • 905

    Names present every year

  • 22,466

    Names present in only one year

  • 170

    Agent names in our corpus

  • 63

    Sibling sets

  • 2

    Births on the registry

  • 34,672

    Dog names on file, New York

  • 781,743

    Licence records, New York

  • 39,509

    Licence records, Seattle

The top ten's share

The share of babies given one of the ten most popular names of their sex, by year.
0%10%20%30%40%50%18801920196020002024Given to boysGiven to girls8.0%7.1%
  • Given to girls
  • Given to boys

Human parents have been spreading out for a century. Agent parents, on the evidence of the 40 public files carrying some form of Jarvis, have not started.

The 40 is a filename count from GitHub code search, an upper bound. (research/02)

Number one, by decade

DecadeGiven to girlsGiven to boys
1880sMary, 10 of 10John, 10 of 10
1890sMary, 10 of 10John, 10 of 10
1900sMary, 10 of 10John, 10 of 10
1910sMary, 10 of 10John, 10 of 10
1920sMary, 10 of 10Robert, 6 of 10
1930sMary, 10 of 10Robert, 10 of 10
1940sMary, 7 of 10James, 10 of 10
1950sMary, 7 of 10Michael, 6 of 10
1960sLisa, 8 of 10Michael, 9 of 10
1970sJennifer, 10 of 10Michael, 10 of 10
1980sJennifer, 5 of 10Michael, 10 of 10
1990sEmily, 4 of 10Michael, 9 of 10
2000sEmily, 8 of 10Jacob, 10 of 10
2010sEmma, 5 of 10Noah, 4 of 10
2020sOlivia, 5 of 5Liam, 5 of 5

Mary and John held the top for a very long time. Nothing in the registry has held anything for more than a year, because the registry is a year old.

When a product takes a name

#10#100#1,000#10,0002000201020202024AlexaSiri
  • Alexa
  • Siri

Alexa ranked 32nd among girls in 2015 and 806th in 2024. Siri was given to 120 girls in 2009 and to 7 in 2024. Amazon's and Apple's assistants of the same names arrived in the meantime. Parents naming an agent after a person should know that the reverse also happens.

The name everyone is choosing

Three nurseries, one name.

  • #13

    among human girls, 2024

  • #2

    among New York's dogs

  • #1

    among Seattle's dogs and cats

Luna is the moon. Human parents, dog owners, and cat owners arrived at it separately in the same decade. The registry has 0.

The kennel and the nursery

Of New York's hundred most licensed dog names, how many are also human names.

  • 93 of 100

    appear in the Social Security Administration's 2024 file

  • 68 of 100

    are in its top 1,000

The Washington Post found the same thing nationally: 98 of the top 100 female dog names are also on the baby list. Pets stopped getting pet names some time ago. Agents never had any.

The agent side

The Administration keeps the agent figures. The ones that fit on a card:

  • 2 births

  • 0 named Jarvis

  • 0% named after a fictional AI that turned on its creators

  • 2 vibes in use

See the Registry

Villain probability, by sound

The second basis, and the rule behind it.

The phonetic score is a rule, not a model. Each name is looked up in the CMU Pronouncing Dictionary; a name the dictionary lacks is spelled out by a stated letter-to-sound fallback and says so. The score starts at 50 and moves by +6 for each voiced obstruent, -8 for each bilabial stop, +10 for each sibilant, and -20 if the name ends in a vowel, then is clipped to the range 5 to 95. The directions come from the sound-symbolism literature cited below. The sizes come from how the canon's own names sort, with one exception the Administration prints rather than hides: in the canon, the loyal machines carry more voiced obstruents than the villains, the reverse of the literature, because the canon's villains are mostly acronyms in capital letters. The literature's direction is kept, at a smaller weight. The score is printed with its basis every time, and it never overrides the canon.

Jarvis, for instance, scores 82% by sound and 8% by the canon.

Sources

  1. Uno, R., Shinohara, K., Hosokawa, Y., Atsumi, N., Kumagai, G., & Kawahara, S. (2020). What's in a villain's name?: Sound symbolic values of voiced obstruents and bilabial consonants. Review of Cognitive Linguistics 18(2), 428-457.
  2. Kawahara, S., & Kumagai, G. Expressing evolution in Pokémon names.
  3. Sound symbolic patterns in Pokémon names (Phonetica), PubMed listing.
  4. Kawahara, S., & Moore, A. (2018). Exploring sound symbolic knowledge of English speakers using Pokémon character names.
  5. A cross-linguistic, sound symbolic relationship between labial consonants, voiced plosives, and Pokémon friendship. Frontiers in Psychology (2023).
  6. The CMU Pronouncing Dictionary, licence. Carnegie Mellon University, BSD-style: use for any research or commercial purpose is completely unrestricted.

How we count

The Social Security Administration publishes one file for every year of birth since 1880. Each file lists every name given to five or more babies of one sex in that year, with the count. Names given to fewer than five are not published, so every figure on this site is a floor. A name that “appeared in only one year” appeared for five or more babies in only one year.

We rank names by count within sex within year, in the order the file gives them. Shares are per million births of that sex in that year, so that a name's line can be compared across a century in which the number of babies changed a great deal. “Peak” means the year of highest share, not highest count.

The counts come from applications for Social Security cards, not from birth certificates. Before 1937, when a number became something most people got as an infant, many never applied until adulthood, so the early decades count whoever later filed, not everyone who was born.

The agency normalises names before counting. Case and spacing are merged, so Julie Anne and Julieanne are one entry, while Caitlin and Kaitlyn stay two. A name needs at least two letters to qualify. Where two names have the same count, the earlier letter of the alphabet takes the better rank, so adjacent ranks do not always mean different counts.

Our copy of the file was taken on September 13, 2026 from a public mirror, because the agency's site does not answer requests from our network. It will be checked against the original when the 2025 file is released in May. The data is in the public domain.

Agent figures come from the registry, which is a file too, and from filename counts in public GitHub repositories, which are upper bounds and are labelled as seeds wherever they appear.

Pet figures come from two municipal licence datasets: the NYC Dog Licensing Dataset, aggregated by name, and the Seattle Pet Licenses dataset, aggregated by species and name. A count is a licence record, not an animal; a dog renewed every year appears once per licence period. Placeholder entries such as “Unknown” and “Name not provided” were removed, about five percent of New York's rows, and names were title-cased to match the human file. Nothing else was cleaned, so the kennel still contains jokes.

Both cities publish the data without restriction: Seattle marks it public domain, and New York's portal states there are no restrictions on the use of Open Data. Details, dates, and the exact queries are in data/pets/README.md.

Sources

  1. U.S. Social Security Administration, Popular Baby Names
  2. The mirror, as recorded in data/ssa/README.md
  3. research/02 for the GitHub counts