|On second thought, I'll take the check.|
But how can I consider only the recognizable thespians? I don't know a good way to do it, so I picked a bad way. I created a "credit score" for each person, which does not at all reflect their quality as a performer, and honestly it's a pretty bad measure of fame, too. But it was something. It goes like this: for each credit they have in a TV episode or movie released in or after 1970, they get a number of points (1 point for a TV episode, 5 points for a direct-to-video movie, 10 points for a made-for-TV movie, and 20 points for a... standard(?)... movie). Anyone with 30 or fewer points was discarded. Maybe I could have linked their performances with ratings, orcounted how far down the cast list they were, or discounted multiple appearances on the same TV show, but I didn't. I did drop everyone for whom I couldn't parse out a first and last name, and people with the 'Jr.' suffix, because they won't fit well in a chain.
|"I'm gonna play it safe. I'll wager $0."|
Now, with only around 428,000 names, and a slightly better (but still terrible) chance of each name being known by an average reader, let's look at some numbers. Here are the basic high-fives:
|Top Five First Names, Actors|
|Top Five First Names, Actresses|
|Top Five Last Names|
In this data set, there are around 285,000 "dead ends" - people whose last name matches nobody's first name. Reedus, Gurira, or Cudlitz, for instance. That means if I picked matching names randomly, there's a 2 in 3 chance at each link that the chain will end there. If I picked each name optimizing for how many choices I'll have after that, it's going to be a very boring chain, full of Michael John, John Michael, Michael Paul, Paul John, John Paul, Paul Michael, and so on. All real people, apparently. It turns out this is a hint about how many branches there are in this system, and why my next idea won't work.
|I opted to avoid a centipede metaphor.|
Perhaps there are still some things at which humans can beat computers. I'll just try doing it by hand.
Ok, maybe not entirely by hand. IWAP that takes a name and lists everyone with that as their first name. IWAP for last names, too. In each case, it sorts the list by yet another score, this one the product of the person's score and the number of choices I would have for the next link. With these programs I can just explore the tree of possibilities manually. Here are some chains I've produced so far:
Michael Shannon Elizabeth Ashley Judd Nelson Franklin
Mia Sara Gilbert Gottfried John Oliver Platt
James Taylor Elizabeth Jordan Elizabeth Taylor James
Clark Gregg Henry Thomas (Ian) Nicholas Brendon
One more idea before I wrap this up. A simple 2-person chain can be used as part of a puzzle. If I give you the first name of one person, and the last name of another, it could clue the name I didn't give you, which they share. For instance, Meg Reynolds would clue Ryan (at least, given the particular set of people I narrowed it down to). In theory, another pair of names could clue another "middle" name, and the middles could be put together, and so on. In practice I think it would be very difficult to construct such a tree of names and have it be solvable by hand. For the simplest 2-person case, IWAP that takes a name and finds unique clue pairs, but once again lots of human intervention is necessary to prune the possibilities. Here are some examples for you to try: