2 ms·
Yep, it uses the same technique. I've pulled every comment and story from HN through the API and make a bunch of Markov chains to produce story titles and comme
by orf 11y ago
Yep, it uses the same technique. I've pulled every comment and story from HN through the API and make a bunch of Markov chains to produce story titles and comments. The input corpus is a lot smaller than subredditsimulator though and the various subreddits have a large variation in the words used (meaning more funny comments), so it's no way near as good.
Perhaps a future enhancement might be to partition comments by the submission domain, i.e use only comments for github.com stories for fake github submissions, might generate very different text than a munge of every comment.
- jedberg 11y agoYou could also use the comments on reddit in /r/programming and /r/startups and other related reddits to help get more data for seeding your corpus. Or if you want to get more complex, find the reddit comments for every link that was submitted to HN and use that (but you have to be careful that you use "hacker" related reddits or it will sound too "reddity")
- captn3m0 11y agoMaybe aggregate over the subreddits listing (where HN links appear) and then whitelist some of them (after checking against a comment frequency count) like programming, linux etc.
- DanBC 11y agoI would love love love it if it could provide comments on a per-user basis. Use my comments for my name, use JohnDoe's comments for their name. As well as keeping comments by submitted domain.