Last week I wrote an article that discussed name popularity since 1880 and included a big, fun database of the Top 1000 male and female names per year. In part 2 of this series, I have a little more Tableau fun identifying the newest, emerging baby names in the U.S.
In part 1 of this series, I described the NABI, which is a naming index my friend and I created in 1988 or so. In this article (part 2), I further examine whether the NABI was real or imagined, as well as determining the modern-day equivalents to the NABI.
One of the trends I first noticed when looking at the name data was that name diversity is increasing, especially since the internet arrived. What this means is that common biblical names are becoming less dominant and unusual names are emerging, for both boys and girls. I was interested in determining the newest emerging names are for both boys and girls in 2015.
The primary goal of this article is to identify which names are rising and falling in popularity. I spent a few minutes in Tableau to isolate both the rising and falling names over the past 10 years (2005-2015).
I figured that a 10-year time slice would be long enough identify the names that are either now in vogue (rising names) or falling out of favor (falling names). Once this was complete, I went back nearly 30 years to the time of the NABI and applied the same techniques to see if the NABI was real or imaginary.
The 2015 Results
Figures 1 and 2 show the totality of the rising and falling names for boys and girls from 2005 to 2015, respectively. This chart simply demonstrates that there are a lot of names for each type of trend. My next goal was to isolate the top rising names and the top falling names for each gender.
The Top Rising Names
Figure 3 shows the top rising names for boys. These names were selected based on having at least a 3 times (300%) increase in popularity from 2005 to 2015. The biggest surprise to me for boys was the name Lincoln. This has the largest percentage increase over the past 10 years, with Karter, Jax, and Ryker also showing big percentage increases.
The name Liam has the most 2015 births of all names having at least a 300% change over 10 years, with Oliver (another surprise) showing impressive results. I wonder what effect the popularity of the actor Liam Nesson has had on this trend. I also wonder why Oliver is gaining popularity.
Figure 4 shows the top rising names for girls. The biggest surprise to me for girls was the name Harper. This has the largest percent change over the past 10 years and is in second place with 10,241 births in 2015. There seems to be a theme to these rising names, with many of them ending in an “a” sound, almost like the name are supposed to be light and airy (Nora, Cora, Luna, Layla, Aria, Valentina, Arabella and Delilah). We night need a new index which we could call the EAI – the “Ending-A Index”.
Top Falling Names
Just as some names are rising in popularity, others are declining in popularity. Figure 5 shows the top boy names that have experienced the largest decline in popularity since 2005. All of the declining names have experienced at least a 70% decline in popularity from 2005 to 2015.
The name Aidan was hit with the double whammy of having the most births in 2015 but also having nearly the largest decline in popularity. Does this mean that the actor Aidan Quinn has lost significant popularity?
I found it hilarious that the name Ashley showed up in this list with the largest number of 2015 births, coupled with greater than a 70% decline in popularity. Ashley, of course, was one-third of our famous NABI index as discussed in the previous article. The biggest losers from a percentage point of view were Megan, Marissa, Breanna, Ciara and Jasmin. I also noticed that several names starting in either A, J, K or L were on this list.
Going Back to the Time of the NABI
This article was finished (but not yet published) when an idea slapped me upside the head. I wondered what the results would be for the time of the NABI (1978-1988) if I applied the same mathematical technique I used in the Figures 3 and 4 above. Specifically, I wondered if any of the NABI (Nichole, Ashley, and Brittany) names would be in the list of the rising girl names from that time.
Figure 7 presents the girl results from the time of the NABI. Wow. Take a look at the two largest blocks. Also notice that the alternate spellings for Brittany (Brittney) and Ashley (Ashlee and Ashleigh) also and made the list.
These alternate spellings are one indicator of how name diversity is increasing over time. People like to join the crowd with popular names, but they also like to introduce some variation on the theme by coming up with alternate spellings.
Just for the fun of it, I also computed the boy names from that time period. Another interesting thing happened.
Figure 8 shows all the popular boys names from that time. What is very interesting to me is that I coached boys in basketball with every one of these names during the decade of 2000-2010. This tells me that these names were even very popular for a few years after 1988.
There is still a lot of investigation left to do with this name database. What I like about this work is that it only takes a few minutes to complete in Tableau and some interesting and unexpected results pop right out of the data.
Tonight Jett, Toni and I were shopping at Kohls. Jett heard the cries of a little baby and asks me if we can see the baby. Well, of course, I say and we head over to the sounds. The baby’s grandmother was pushing the baby boy in a stroller. I asked her how old is he, and she replied 2 months. I then asked her what his name is. She says, “Jaxsen”, spelled with an “e” instead of an “o”, as in “Jaxson”.
I bet you can guess what I did! I whipped out my phone and showed her Figure 3, which shows “Jaxson” in third place for the top emerging boy names. She laughed and asked me how I did that! I laughed and said, I do data analytics on all kinds of things and I just happened to do this analysis a few weeks ago. She said “goodbye, I’ve got to walk the baby!”.
Well, maybe there is some truth to this data analytics thing, including identifying how name diversity is increasing over time.