Additional Info: I asked a large language model, 'On a scale of 1-10, how _______ do you think this YouTube video title is?' for every video.
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How trendy 3Blue1Brown YouTube video titles are correlates with...
Variable | Correlation | Years | Has img? |
The number of layout workers, metal and plastic in Kentucky | r=0.95 | 6yrs | No |
The number of sound engineering technicians in Florida | r=0.94 | 8yrs | No |
Freezing temperatures in Minneapolis | r=0.93 | 9yrs | Yes! |
The number of college sociology teachers in Tennessee | r=0.9 | 7yrs | No |
The number of chiropractors in Mississippi | r=0.89 | 8yrs | No |
Google searches for 'flights to Antarctica' | r=0.89 | 9yrs | Yes! |
Popularity of the 'is this a butterfly' meme | r=0.86 | 9yrs | No |
Season wins for the Baltimore Ravens | r=0.76 | 9yrs | No |
How trendy 3Blue1Brown YouTube video titles are also correlates with...
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You caught me! While it would be intuitive to sort only by "correlation," I have a big, weird database. If I sort only by correlation, often all the top results are from some one or two very large datasets (like the weather or labor statistics), and it overwhelms the page.
I can't show you *all* the correlations, because my database would get too large and this page would take a very long time to load. Instead I opt to show you a subset, and I sort them by a magic system score. It starts with the correlation, but penalizes variables that repeat from the same dataset. (It also gives a bonus to variables I happen to find interesting.)