horsey-books

Nice work! I did something in a similar vein, using JavaScript and Markov chains back in 2015 or so and ended up giving a fun talk about it at a coding bootcamp. [1] I based it off a Ruby module called “Twitter Ebooks”, which I believe was based on a Python module called “horsey books”, which could create a bot that would make posts using Markov chains, given a corpus of text. [2] (I’m not dropping the date to be a jerk, more to point out that Markov chains / n-grams are an interesting concept for experimenting with language models and have been around for a while.) In my case, I fed a corpus of data (my Twitter history at the point, which was something like 20K tweets) and tried to create a Twitter bot to make intelligent sounding posts. It worked out, sometimes. But, it was a lot of fun to figure out! [1] “Building intelligent robots us

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.