From Karen to Katie: Using Baby Names to Study Cultural Evolution

I’m happy to announce that my paper From Karen to Katie: Using Baby Names to Understand Cultural Evolution has been accepted for publication in the journal, Psychological Science. The article also received some press in Time magazine.

In this paper we track the evolution of baby names from 1882 through 2006. First, we demonstrate that names increase in popularity when other, phonetically similar, names have been popular in previous years (the more you hear it the more you like it). Second, we found the effects to be non-linear. In particular over-popularity hurt adoption (think of how annoying it was to have 8 people named Alex in your class, names/sounds can be too popular). Third, we found varying strength in these relationships across name position. The effect was strong for the first phonemes/sounds and less strong for ending phonemes/sounds (often rhyming) and internal phonemes/sounds.

Finally, we confirmed the initial study, by considering the impact of hurricane names on baby name frequency the following year. Hurricane names are a good case study as they are picked ahead of time and effectively an exogenous shock to the system. We found that increased severity (which correlates with increased mentions), yielded larger increases in frequency of similar names the following year.

This paper was a fun exercise in Bayesian Hierarchical Modeling. I’ll call it a zero inflated poisson regression, with all the usual priors.

We received a shout out from Wharton, which is always fun.

If you want to build models like this or read up on Bayesian Statistics, here are 3 suggested books:

• Bayesian Data Analysis – This is THE book in Bayesian Statistics. Its a bit theoretical for those without a math background, but is amazing and if you want to really learn Bayesian Stats you should start here.
• Bayesian Modeling Using WinBUGS – We fit our models using WinBUGS, this is a solid intro.
• Data Analysis Using Regression and Multilevel/Hierarchical Models – This book is more applied than Bayesian Statistics. It has great examples, though is a little light on the details/theory for my taste