I'm trying to make social media moderation more democratic and using that to decide fuzzy questions like "should this post be censored", or "is this misleading" [0]. While the crowd's answer won't be perfect it will help sort through a lot of the noise and feel better than the decision of whatever mod happened to create the subreddit. The problem: how can I make decisions based on a sample with a binary question. I t…
I worked on a similar idea last year. What I did was take urls to content, scrape the content, and pipe it through a machine learning a evaluator to apply various labels and warnings to content. Lastly, add some nice embeddable UI to surface the report. I got it to a decent state, but didn’t know how to propagate it or inject it into social communities. I wanted people to be able to tag it on Facebook, and it would r…
I feel like machine learning isn't at the level where it can tell if something is misleading, unless it's from a known sketchy source.