why is the prize so small when the economic benefit could be much larger?
Stack Exchange Machine Learning Contest
61–67 of 67 posts
Re: Stack Exchange Machine Learning Contest
#62Earlier quoted context omitted.
"They had a preconceived notion of what StackOverflow Is and they are going to stick to it, users be damned." Which is why the site is hugely successful. If you want discussion then do it here or on Reddit. I don't want the questions I ask about why something doesn't work in jQuery or C# or C++ or whatever drowned out by Ruby Vs Python posts or stuff like the question cletus mentioned above, or "what have I got in my…
"Which is why the site is hugely successful." You and Jeff are confused about what makes stackoverflow.com successful. The reason stackoverflow is successful is because it's a clone of another successful tech Q&A site (experts-exchange.com) minus the scummy answer cloaking plus some social voting. That's it. All this stuff about the "right kinds" of questions being "key to its success" is based on absolutely nothing.…
Look at Reddit vs HN, do you think the difference is down technology ?
On multi-sided market websites (marketplaces, forums, ugc sites, etc) community management is generally a far bigger differentiator than technology. Quora isn't better than Yahoo Answers because of it's technology, but because of it's community.
My guess is that SO wants to steer away from subjective questions which can lead to downward spiralling in quality (i.e. language/tool-chain wars) which can then have a knock-on effect on what type of behaviour users think is acceptable across the rest of the site (i.e broken window syndrome).
Re: Stack Exchange Machine Learning Contest
#63Earlier quoted context omitted.
This: Your goal is to build a classifier that predicts whether or not a question will be closed given the question as submitted.
Everyone seems to have skipped right over this: "In a perfect world, we'd be able to offer specific, targetted guidance for authors whose posts were likely to be shot down, before they ever showed up on the site, and without requiring as much up-front effort from our community." Which is waaaaay before the classification line.
So you're wanting to use an automated system (which one might loosely term a bot) to prevent content from being displayed without having to have that content moderated by humans.
How is that not replacing moderators [in part] with "bots"?
Re: Stack Exchange Machine Learning Contest
#64Earlier quoted context omitted.
Everyone seems to have skipped right over this: "In a perfect world, we'd be able to offer specific, targetted guidance for authors whose posts were likely to be shot down, before they ever showed up on the site, and without requiring as much up-front effort from our community." Which is waaaaay before the classification line.
So you're wanting to use an automated system (which one might loosely term a bot) to prevent content from being displayed without having to have that content moderated by humans. How is that not replacing moderators [in part] with "bots"?
Because it's not making the final decision on weather a question will be allowed or not. It just aids in providing the user advise about how to improve the question even before the user has asked it.
The problem right now is that the user mostly has very little opportunity to improve his question, because most of the time it has already been closed, and has very little chance of getting opened again (unless the question is flagged for moderator attention).
Re: Stack Exchange Machine Learning Contest
#65Earlier quoted context omitted.
Worth a try in the name of science, but I'm pessimistic about the ability of machine learning to measure subjective "quality" of a question. In the best case you'll end up with a txtspeak and Proper English detector. But I knew that already.
I'd be interested to see if there's any predictors for "good quality" questions vs anything else. Some research project for students, perhaps. I remember reading something about telling the difference between truthful and fake reviews. ( http://cornellsun.com/section/news/content/2011/09/23/cornel... ) There's more literature in this paper. ( http://www.cs.uic.edu/~liub/publications/WWW-2012-group-spam... )
I think a useful metric will be the time-to-first-answer and rate of submitted answers. These will be the answers to badly-researched questions á la "How do I get all the buttons on this page?[jQuery]".
Unfortunately, that is a post-question signal, and won't be able to be used in the context of the competition.
Re: Stack Exchange Machine Learning Contest
#66All those people, who helped in generating data for machine learning algos, now may feel fooled, like suckers.
Re: Stack Exchange Machine Learning Contest
#67It's nice to see this kind of contest but the topic just sets me off on a much-needed rant. The moderator situation on Stackoverflow is getting out of control. I see a Q&A site as having three main groups: 1. People who ask questions; 2. People who answer questions; and 3. People who edit/moderate questions. Even 2+ years ago there was a lot of lip service paid to the value of (3). I disagreed then and it's only been…
That's why this has to happen on Kaggle. If they asked it on SE there was the danger of one of their mods closing the question.
There is the claim that people will have a worse experience if generic like comparative questions are allowed. A machine learning contest attempting to verify this claim would be more important. Or they could simply ask this on stackoverflow? Maybe there will be enough answers before somebody sends it to oblivion (meta stackoverflow site) or closes the question.