I also have some serious consideration of whether we ought to be trying to come up with a way to filter out "curation trains" of followed auto voting, but I haven't come up with a really good way of detecting that sort of event. My gut says that some sort of clustered timeseries would be about the only way to determine or detect a relationship between events like that, but it's hard to say for sure.
The system does not make it very easy to analyze votes by value and aggregate, so this is always a lot of fun.
I've actually been trying to implement a filter that would simply bias presentation in favor of things that I have personally voted up in order to provide an additional form of weighting and presenting the content available on the blockchain, but that's been going slowly at best. I know that any kind of filtering is a big task.
In this case, because up vote bots are nearly impossible to detect if they're not on the big listings, I'm not sure that it's absolutely useful to trying correct for them specifically as opposed to individualizing the experience of a user who is already involved in seeking out content that they like and signaling to the system that they do. After all, it's theoretically possible that someone might like the kind of content that is consistently voted up by a bot. I hate to make that kind of assumption up front. It's theoretically possible that, at some point, someone might create a bot which consistently votes up content that I'm interested in. Theoretically.
(You really have a bunch of friends who like to follow you around and flag everything you do, don't you? I don't think that I've ever seen a comment with a reasonable content like that get so absolutely stepped on as hard as feet could go. It's really quite impressive. No one cares that I'm a thorn in their side so much that they follow me around quite so slavishly. Good job!)
yep cos I had ran part of the report for 2017. it is now updated
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You're correct!
6k SBD is closer to the daily upvotes by the top 11 bid bots, not for the whole period.
updated, they were ran for 2017 instead of 2018
thank you @doodlebear I have now updated.
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I also have some serious consideration of whether we ought to be trying to come up with a way to filter out "curation trains" of followed auto voting, but I haven't come up with a really good way of detecting that sort of event. My gut says that some sort of clustered timeseries would be about the only way to determine or detect a relationship between events like that, but it's hard to say for sure.
The system does not make it very easy to analyze votes by value and aggregate, so this is always a lot of fun.
I've actually been trying to implement a filter that would simply bias presentation in favor of things that I have personally voted up in order to provide an additional form of weighting and presenting the content available on the blockchain, but that's been going slowly at best. I know that any kind of filtering is a big task.
In this case, because up vote bots are nearly impossible to detect if they're not on the big listings, I'm not sure that it's absolutely useful to trying correct for them specifically as opposed to individualizing the experience of a user who is already involved in seeking out content that they like and signaling to the system that they do. After all, it's theoretically possible that someone might like the kind of content that is consistently voted up by a bot. I hate to make that kind of assumption up front. It's theoretically possible that, at some point, someone might create a bot which consistently votes up content that I'm interested in. Theoretically.
(You really have a bunch of friends who like to follow you around and flag everything you do, don't you? I don't think that I've ever seen a comment with a reasonable content like that get so absolutely stepped on as hard as feet could go. It's really quite impressive. No one cares that I'm a thorn in their side so much that they follow me around quite so slavishly. Good job!)