Happy third birthday, Horse_ebooks

same to you

dur fitay muu

As the name vaguely alludes to, a lot of the text is extracted from ebooks, including public domain ones from Project Gutenberg. That said, I find it hard to believe that just picking random sentence fragments would give such a high signal-to-noise ratio, so there's probably something else going on.

If I were the one pulling the strings of Horse_ebooks, I would probably focus on building a statistical model that uses the number of favorites per tweet as its training data, and looks for linguistic features that are highly correlated with getting lots of favorites.

It reminds me of the Cornell boxes created by Neuromancer and Wintermute

Here's more code for running your own: https://github.com/longears/horsey-books It's running the (NSFW) bots @fetlife_ebooks, @obscuregenres, and @snes_games.

Lately I've been tweaking and curating the output before posting it. It makes it a bit less magical but much funnier. It turns out that seeding your brain with random starting points like this is a potent creativity-boosting technique.

I tried using Bayesian spam filtering to classify the results as Funny or Not Funny, but it was unable to detect funniness just from which words were present in the message.