This is (weirdly) common in production ML codebases written by software engineers. Like you, I have no idea why unless it's a memory optimisation (where you count 4+ as many).
Having every column as a boolean (0/1) means you can treat it as a bitmap. As an (entirely fictional) example, imagine if you wanted to get the features of a thread instead of a single tweet. You could do it as a union of all the tweets:
Ok that makes lots of sense from an engineering perspective. It's pretty insane from a statistical perspective though, which I think was the original point.
