The past 80+ comments from me have all had at least one downvote. There is no reasonable way to interpret this other than as having a stalker.
And the solution to how not to catch false positives is to use some common sense. You’re never going to have an automated algorithm that can detect every instance of abuse, but even an instance that is not detectable by automatic means can be detectable if someone with sufficient database access takes a look when it is pointed out to them.
There is no reasonable way to interpret this other than as having a stalker.
Suppose we find the list of users who downvoted your recent comments, and there are fifteen users on that list, each of whom is an active poster in their own right. What conclusion would you draw from that?
(It may be that, when we actually find that list, there is one account, or a handful of mostly inactive accounts, that represent almost all of the downvotes, in which case ‘stalker’ is a reasonable conclusion. But it’s not the only way the data could turn out.)
And the solution to how not to catch false positives is to use some common sense.
Common sense is costly. The point to doing this algorithmically is that you get a query result that says “these are the twenty cases that might be karmassassination” instead of “these are the twenty thousand cases that might be karmassassination” or “these are the zero cases that might be karmassassination.”
It’s also not particularly wise to run this check just on people who complain- part of the point of this is to prevent karmassassins from driving users away, which hasn’t happened to the people who stuck around to complain (somewhat)- and at least a few users have a habit of downvoting any comments complaining about karma loss because they don’t like comments that complain about karma loss, and so they’ll be extra likely to show up on that list.
Suppose we find the list of users who downvoted your recent comments, and there are fifteen users on that list, each of whom is an active poster in their own right. What conclusion would you draw from that?
I’d conclude that this is an extremely weird statistical anomaly which is not one user moderating down comments, but looks almost exactly like it is. One user doing a lot of downmods has to apply the downmods to separate comments, so his downmods are spread out. 15 users producing the same total number of downmods independently of each other would produce something a lot closer to a Poisson distribution with an expected value of 1, and there should be a number of comments that have zero downmods just by chance.
And the solution to how not to catch false positives is to use some common sense. You’re never going to have an aytomated algorithm that can detect every instance of abuse, but even an instance that is not detectable by automatic means can be detectable if someone with sufficient database access takes a look when it is pointed out to them.
Right on. The solution to karma abuse isn’t some sophisticated algorithm. It’s extremely simple database queries, in plain english along the lines of “return list of downvotes by user A, and who was downvoted,” “return downvotes on posts/comments by user B, and who cast the vote,” and “return lists of downvotes by user A on user B.”
It’s extremely simple database queries, in plain english along the lines of “return list of downvotes by user A, and who was downvoted,” “return downvotes on posts/comments by user B, and who cast the vote,” and “return lists of downvotes by user A on user B.”
And then what will you do with that data? If you find that GrumpyCat666 cast most of the downvotes, does that mean that GrumpyCat666 is a karmassassin, or that GrumpyCat666 is one of the gardeners?
(I can’t find the link now, but early on there was a coded rule to prevent everyone from downvoting more than their total karma. This prevented a user whose name I don’t recall, who had downvoted about some massive fraction of all the comments the site had received, from downvoting any more comments, but this was seen as not helpful for the site, since that person was making the junk less visible.)
The past 80+ comments from me have all had at least one downvote. There is no reasonable way to interpret this other than as having a stalker.
And the solution to how not to catch false positives is to use some common sense. You’re never going to have an automated algorithm that can detect every instance of abuse, but even an instance that is not detectable by automatic means can be detectable if someone with sufficient database access takes a look when it is pointed out to them.
Suppose we find the list of users who downvoted your recent comments, and there are fifteen users on that list, each of whom is an active poster in their own right. What conclusion would you draw from that?
(It may be that, when we actually find that list, there is one account, or a handful of mostly inactive accounts, that represent almost all of the downvotes, in which case ‘stalker’ is a reasonable conclusion. But it’s not the only way the data could turn out.)
Common sense is costly. The point to doing this algorithmically is that you get a query result that says “these are the twenty cases that might be karmassassination” instead of “these are the twenty thousand cases that might be karmassassination” or “these are the zero cases that might be karmassassination.”
It’s also not particularly wise to run this check just on people who complain- part of the point of this is to prevent karmassassins from driving users away, which hasn’t happened to the people who stuck around to complain (somewhat)- and at least a few users have a habit of downvoting any comments complaining about karma loss because they don’t like comments that complain about karma loss, and so they’ll be extra likely to show up on that list.
I’d conclude that this is an extremely weird statistical anomaly which is not one user moderating down comments, but looks almost exactly like it is. One user doing a lot of downmods has to apply the downmods to separate comments, so his downmods are spread out. 15 users producing the same total number of downmods independently of each other would produce something a lot closer to a Poisson distribution with an expected value of 1, and there should be a number of comments that have zero downmods just by chance.
Right on. The solution to karma abuse isn’t some sophisticated algorithm. It’s extremely simple database queries, in plain english along the lines of “return list of downvotes by user A, and who was downvoted,” “return downvotes on posts/comments by user B, and who cast the vote,” and “return lists of downvotes by user A on user B.”
And then what will you do with that data? If you find that GrumpyCat666 cast most of the downvotes, does that mean that GrumpyCat666 is a karmassassin, or that GrumpyCat666 is one of the gardeners?
(I can’t find the link now, but early on there was a coded rule to prevent everyone from downvoting more than their total karma. This prevented a user whose name I don’t recall, who had downvoted about some massive fraction of all the comments the site had received, from downvoting any more comments, but this was seen as not helpful for the site, since that person was making the junk less visible.)