Hi,
Thanks for your response. The Proof of Tipping model is interesting and it has several advantages:1. unlike 'likes' and upvotes, tipping uses scarce resources, which encourages careful consideration of quality by the tipper2. it gives people who tip a stake in the content they tip, which incentivizes those people to help promote said content
I see the following problems though (you mention one of them) if tipping is also intended as a form of content curation and hence of trying to predict what content will be successful.
I think this function is important (and I think it is implicit in the Proof of Tipping model by giving more weight to early tips (which in a sense is the assumoption that future consumers are likely to appreciate the content about as much as the early consumers))) because LTB has to have a way of selecting content so that content that is more likely to be popular will be promoted (by being shown on the "front page" for example) while low quality content that is unlikely to be popular should not get in the way of the audience that only wants to see high quality content.
If tipping is also used as a way to predict which content will be popular (and so not just to reward content and to measure 'afterwards' how successful said content was), then it runs into the following problem
1. In the 'proof of
tipping' (POT) model tipping really is an untenable hybrid of tipping
and predicting/investing. Normally tipping is the expression of a
personal preference. I tip an article because I thought it was great.
Predicting/investing on the other hand is a way of trying to get a
ROI by predicting better than other people do some future event. In
this case the event is the relative popularity of an article and thereward comes in the form of newly issued LTBcoins.
reward comes in the form of newly issued LTBcoins.
The problem is that these
two different natures can pull in opposite directions. For example,
it makes sense for me to predict/invest in an article because I think
a lot of other people will like the article even though I myself may
think the article is not very good. And conversely, it makes sense
for me to tip and article if I think it's great even though I thinkfew others would agree with me.
few others would agree with me.
In the first case the
predictive function undermines the expressive function and in the
second case the expressive function undermines the predictivefunction.
function.
2. The system can be
manipulated by somebody (or a group of people) tipping their own
article as much as possible, undermining both the predictive and theexpressive functions.
expressive functions.
