It still doesn't solve the problem that for someone to _find_ those great comments, they have to _read_ them, and stop them from getting buried.
I'll err on the side of caution with revealing employee counts, but in my experience many of the FP/Atlantic/Mother Jones/Weekly Standard/Pick your midrange site are running on a single digit to low double-digit number of web production staff, many of whom are also trying to make a writing, article layout, or fact-checking quota. The suggestion that these magazines can either get those staffers to moderate tens of thousands of comments per day, or quadruple their web staff just to improve the comments ignores the business reality.
User moderation in the normal HN/Reddit way doesn't work well on news sites, it's too easy to game or brigade, and news sites can't or won't give add unpaid moderators to be gatekeepers.
That's what's hard; creating comments is scalable, filtering them is not. Leaving them unfiltered doesn't work either.
>I think that incentive [is good], particularly when you're trying to draw subject matter experts.
You bring up an excellent point. One of the fundamental problems with comments, I think, is that it creates a space in which ignorance and expertise are equally-weighted. In fact, it's often worse than that for reasons we all know: interesting issues are hard to distill into 300-or-so characters, and short, simple points are often more percussive.
Vetting credentials is a very good option IMHO for certain forums but not for others. Reddit's /r/askscience is an example of a forum in which it works well.
>It still doesn't solve the problem that for someone to _find_ those great comments, they have to _read_ them, and stop them from getting buried.
I wonder if this problem can't be solved through the use of machine-learning to classify comments into high-versus-low quality by grammatical and semantic analysis. This kind of first-pass filtering could, at the very least, help throw out the obvious trash and pre-select candidates for recognition.
Such a system can be tuned to minimize false-alarms (shitpost getting flagged as good), which I think represent the most problematic of classification errors. This is a nice problem-space for ML because the increase in misses implied by a bias against false-alarms doesn't degrade the service much: not having one's comment select for re-publication is unexceptional.
Thoughts?
The cultural issue is that many news orgs are still run by people for whom the idea that technology could accidentally censor a valid criticism or ban a decent voice is just too risky. I think this is changing, and many newsrooms today a little more fluid than when I really cared about the problem 4 years ago.
The tech issue is a little bit of a cop out on my part. An ML approach is super attractive to me as a techie. Google (youtube), facebook, NYT, WaPO, and tons of other billion dollar orgs have this problem, and could loads of money by being seen as better communities.
On the more guerrilla side, hundreds of subreddits have automoderaters written by savvy, caring moderators.
They have terabytes of training data, already tagged, and world class ML experts on staff. If it was a tractable problem with business value, why wouldn't they have fixed it? I'm guessing it's the sort of thing that looks doable from the surface, but you get buried in the details.
Again, cop out answer, so please go prove me wrong!!
I understand, and I think that's probably the most difficult problem of the two. I'd just like to point out -- in the interest of discussion -- three things:
1. Pre-filtering for moderators is different (much safer) than auto-banning by a bot
2. It's valid both to filter informed opinions that are poorly expressed, and for a publisher to have a preferred "voice", i.e. a style of writing that it favors.
3. The argument can be made that machines are no more biased than human editors, and that in many cases, the biases of the former are known. As a corollary to this point, there exist certain ML techniques (e.g. randomized forrest classifiers) for which the decision process of an individual case can be retraced after the fact.
How do you think publishers would respond to these counter-points?
>technical problem
Counter-cop-out: someone has to be the first!
Somewhat-less-cop-outy-counter-cop-out: by your own admission, certain sites (e.g. Reddit) have high-quality automoderators.
I would argue that the problem is "approximately solved" and that this is sufficient for the purposes of moderating an internet news publisher. Again, I would make the signal-detection-theoretic point of my previous comment: I can selectively bias my automoderators in favor of reducing either false-alarms or misses. Of course, this brings us back to the cultural problem you mentioned.
By this I conclude that the bottleneck is cultural, which brings me to a follow-up question: what do you think is driving the increased tolerance towards accidentally censoring a "decent voice"? Is it the understanding that it doesn't matter so long as a critical mass of decent voices are promoted?
> How do you think publishers would respond to these counter-points? In my experience 1 and 2 are fine, but 3 is actually a _net negative_ to some of them. People who by and large have come up through 10+ years of paying dues in a 'The patrician editor is always right' culture _hate_ giving up control, even when it makes their jobs easier.
Editors I've seen have balked at things like Taboola and outbrain, despite them being test-ably better than human recommendations, and saving staffers work. It's a fair argument that picking which stories to promote is a core part of the editorial job more so than comment moderation, but the attitude match is there. Editors at one DC media org I didn't work for shot down A/B testing any new features in the first place, because there was an assumption that the tech staff would rig it!
I don't want to paint 'editors' with too broad a brush, but there's definitely a cultural reluctance at the high level to automated decision making.
> What do you think is driving the increased tolerance towards accidentally censoring a "decent voice"? Is it the understanding that it doesn't matter so long as a critical mass of decent voices are promoted?
It doesn't matter to you and me. We think like HN'ers, where there are trillions of internet packets flowing around every day, and a few will get lost. They think like hometown newspaper editors parsing letters. When you take on the responsibility of being a gatekeeper, screwing it up is a big problem, every time.
I think increased tolerance is coming from more exposure to the sheer volume (Every week at FP the website gets more visits than people who have ever read the magazine in it's 50 years of existence combined), and a bit of throwing the hands up and saying "who knows"
Again, I'm speaking for a pretty specific niche of old-school newspapers and magazine people turned editors of major web properties, because those are where my friends work. Things are probably different at HuffPo or Gawker or internet native places, but clearly not that different because their communities are still toxic.
> I would argue that the problem is "approximately solved" So I disagree here, but don't have evidence to back it up, other than years-old experience with Livefyre's bozo filter, which we didn't put enough work into tuning to give it a super fair shake.
Taking spam comments as mostly solved, I think there are 3 core groups of 'noise' internet comments:
1. People who don't have the 'does this add to the discussion' mindset to use HN's words. cloudjacker and michaelbuddy 's comments below demonstrate this pretty well. I'd lump cheapshot reddit jokes in here as well. They're not always poor writers, or even negative -- "Great article! love, grandma". Which falls back into the ethics of filtering them. I suspect that this is 80%+ solveable.
2. The 'bored youth' and 'trolls' group. This is actually the worst group I think, because these are the people I suspect that make death threats and engage in doxxing and swatting. Filters will catch some of these people, but they're persistent, and many of them are tech-savvy and reasonably well educated. They can sometimes be hard to tell from honest extremists. A commenter from group 1 who is personally affronted can fall into this group, at which point they become a massive time suck. Hard to solve, but verified accounts help here in the US case.
3. Sponsored Astroturfing. Russia, Turkey, (pro/anti) Israel, China, Trump (presumably the DNC?) all have a large paid network of people just criss crossing the internet all day trying to make their support base look larger than it is. Especially in the US politics case, they often speak good english, and are familiar with both sides' goto logical fallacies. They'll learn your moderating style in a heartbeat, and adapt. Unsolveable.
Anyway, if someone builds a good bozo filter, they're almost certainly a zillionaire. I hope it happens, but I suspect we'll just start looking back on website comment sections like usenet, as a good idea that didn't scale very well, and find something better.
It's pathetic bottom-feeder crap.
Maybe if I fed the beast through tracking, I'd see higher quality recommendations, but I won't, and I don't. They only serve to tell me just how precariously miserable the current state of advertising, tracking, surveillance-supported media is. I'm hoping it will crash and burn, not because I want present media organisations to die, but until they do, we don't seem to stand any chance of something better.
(What better, you ask? Information as a public good, supported by an income-indexed tax.)
I agree that the '10 weight loss secrets' promoted junk to third party sites is bottom scraping.
Sufficiently that the in-site referrals fail for technical reasons.
Perhaps the comments sections for journalistic pieces from organizations like Ars, NPR, NYT, local news, etc could be more of a competition (like Slashdot). Top 300 comments get preserved, leave it open for a month with no comment limit and some light moderation, and let the conversation go wild (I like Reddit's system for this), then delete all but the top 300 at the end.
Adjust "300" and "top" to fit your organization's needs, just make sure they're clearly defined. Would also help limit the scope for an ML-based solution, too. :)
Moderators would still be needed but their workload would be reduced. And there would be money available for them since many would subscribe / donate just to be part of the community, which would make moderation less of a drain and more of the core profit-making.
I don't think you're correctly identifying the problem. In my experience, the problem with comments, especially on news sites, is a glut of bad comments, rather than a lack of good comments. This solution doesn't disincentivize bad comments.
slashdot nailed moderation, no one has attempted something similar. most systems are simple up/down vote or like/report
i am also starting to wonder if the agegroup being hired to implement "social" for websites is now young enough to have missed slashdot in it s prime.
the fact that people are still brainstorming from scratch instead of talking about how to improve slashdots model reeks of reinventing the wheel because they never heard of it.
That's me! Can you explain the Slashdot model and why it worked? Or point to a good write up about it somewhere else?
Slashdot's model was perhaps a little overcomplicated, but my favourite feature was the ability to tag up/down votes with flavours. +1 Informative was different to +1 Funny, and "Factually incorrect" was a different downvote to "Off-topic spam" (whatever they were called).
Other quirks off the top of my head: it capped at +5 and ... -1, I think? The score represented a thing closer to the up/down ratio than "Facebook likes". There was a dedicated -1 Overrated moderation for "I don't disagree that it's interesting, just not +5 interesting".
Also, logged in users got a fixed number of moderation points at random intervals, and you couldn't moderate in a story that you commented in. I'd like to believe this discouraged "throwing away" points on low-effort joke comments, but I'm not sure the facts of Slashdot comments entirely bears that out.
EDIT: And then there was meta-moderation...
especially all the Moderation, metamoderation, and Karma sections!!
A great deal of high-quality commentary was buried, however, often the best and most informative. That's fairliy much par for the course.
Much the early vibe on the site came from the fact that it was simply where intelligent people were commenting online -- especially the early Free Software crowd (well, early in terms of Web 1.0 -- there was the whole 1980s and early 1990s contingent as well).
ESR (before he went fully whackjob mode), Ted T'so, Alan Cox, Bruce Perens, Rasterman, and others.
Much that group seems split amongst HN, LKML, LWN, and Google+ these days, along with some blogs.
I'm about ready to blackhole that domain.
Needless to say an event happened and was reported the next day, so it could be a whole week between the Trump-of-the-day saying something and comment appearing about it. All of this would be filtered by the 'editor', however you did have frequent letters by the likes of Keith Flett, who somehow got his letters published more often than the other 3-5 million readers (as it was back then, just UK sales with poor distribution in places like Birmingham).
There were no 'likes' back then so you had to have something to say to bother writing in.
How do we get a digital equivalent? I don't buy the dead-tree paper these days so no idea if 'letters to the editor' still exists, but, back then it was good, very good.
I assume it would kill some collaboration/innovation like on HN or a meaningful subreddit, but maybe no one really ever has anything meaningful to say when reacting to general news...
I guess it would also produce duplication from many people not knowing something was said already (however, the duplicate reactions could be monetized later down the line maybe...)
The podcast is .NET Rocks and their comments seem to be pretty good overall.
As such, bias and opinion is welcome, provided that it's analytical, verified by fact to a reasonable degree, and respectful of common etiquette. The genius in this approach, as far as I'm concerned, is that it manages to preserve the original purpose of comments: scalable content-generation!
Clearly, moderation is a Hard Problem, but one that I think benefits from an economic/incentives analysis. One conclusion I've drawn is that restricting comments to paid-consumers makes banishment and sock-puppetry costly enough that moderators can mop up the rest by hand.
To ask a specific question: what, exactly, remains "hard" with this approach? Do you think "free to read / pay to comment" is viable, in principle? Do you think the promise of publication is not a good incentive? Why?