Analyses of Baby Name Popularity Distribution in U.S. for the Last 131 Years

TL;DR

This study analyzes 131 years of U.S. baby name data, revealing that name popularity distribution fits a combined Beta and power-law model rather than traditional Zipf or Beta models alone.

Contribution

It introduces a novel empirical model combining Beta and power-law functions to accurately describe baby name popularity distribution.

Findings

Name popularity follows a piecewise distribution with Beta and power-law components.

Neither pure Zipf's law nor Beta distribution alone fit the data well.

The combined model provides a better fit for the entire dataset.

Abstract

We examine the complete dataset of baby name popularity collected by U.S. Social Security Administration for the last 131 years (1880-2010). The ranked baby name popularity can be fitted empirically by a piecewise function consisting of Beta function for the high-ranking names and power-law function for low-ranking names, but not power-law (Zipf's law) or Beta function by itself.