With the influx of new users in the past month, it has become progressively more difficult for new content to be seen by curators of significant weight. Some of it is to be expected: with growing userbase comes increased competition. In this post, I highlight some of the issues new users might be facing and propose a possible implementation of an incentivized downvote system, which I believe directly improve the situation.
In current system an “upvote only” culture is promoted, due to the lack of rewards and the negative stigma behind downvoting (flagging). This creates an environment in which more visibility almost certainly equates to higher payout. It can seem like a win-win situation, but taking a step back can help us to see how it objectively affects the Steemit ecosystem. The following statement can’t be emphasised enough:
In a zero-sum game in which a fixed amount of Steem is created every day, an upvote for one article is equivalent to downvoting every other article (of lower weight).
As a result, on the present platform, each upvote shouldn’t be merely viewed as a user’s appreciation for a given post, but rather as a statement signifying their preference for said content over all other. This is a glaring issue, as no curator should be able to pre-judge and lower access of content they haven’t seen to others on the website.
Since the money used as rewards isn’t taken directly from the voter's wallet, it may feel to them as though they’re handing out free cash with minimal effort and no consequences for unwise curation. Looking at the bigger picture, however, it is clear that everyone pays for such actions in several ways: lower content quality, limited scalability and centralization (content/payout/curation power) come to mind. All of these can contribute to the decline of the platform, or at least impact its growth in a significant way.
Inflated payout for content A entails that some other content B is underpaid. This means that lower quality content can make it to the trending/hot page for everyone to see. Similarly, this leads to a ranking system in which the creator of content B doesn’t get their deserved visibility, one that accurately reflects the quality of their content.
Visibility and the high disparity in payouts has been a hot topic in the past couple of weeks. These are real problems that need our attention as a community. Here’s a discussion between @teamsteem, @fyrstikken and @stellabelle in which they briefly talk about the issue. Here’s @dan acknowledging the visibility issue.
If you’re not convinced yet, there are two very good examples of articles that were posted twice. After going unnoticed at first, they were reposted by another user who recognised their value. The first one was featured in @stellabelle’s secret writer (she discusses it here) and the second one is mentioned in this post by @coinbitgold. These examples either demonstrate the high dependence on luck or the poor performance of the ranking system in assessing value. Either way, the situation is far from optimal.
Centralization (of content, payout and curation power)
The current system promotes name recognition more than content quality, which has a direct impact on centralization. Those who make it to the top trending page are much more likely to get there again, even with subsequent lower quality articles. Lower diversity leads to content centralization and an increase in their SP holdings. In turn, this increases their influence in selecting new content. For instance, a community based around cryptocurrency is more likely to upvote cryptocurrency content, leading to a much higher percentage of cryptocurrency related articles than there is on any other social media. This can be positive for building and reinforcing ideas in a small community of experts, but not when trying to appeal to a larger population of diverse interests.
How important exactly is platform growth? If you read the Whitepaper, you'll recall Metcalfe's law: the value of a telecommunications network is proportional to the square of the number of connected users of the system (n^2). This was shown to hold for large social networks like Facebook and Tencent. Read more here..
Assuming those numbers hold in the long run, we have
Market Cap ≈ 0.22 * n^2
This means that a 10% increase in number of users should lead to an increase in Market capital of approximately 21% (110%^2). Looking at it this way, large SP holders should spend most of their efforts trying to make the platform more welcoming to new users. Reducing the payout gap would certainly help towards that.
With the current voting system, most of the daily mined Steem for content creation and curation gets distributed among users on the top trending/hot pages. This is to the detriment of the majority of posts (close to 4000/day) that get close to nothing. I invite you to listen to this excerpt from Free Talk Live in which @ftlian discusses his first experience and perception of the trending page as a new user.
At the time of this post, 87% of all articles have received less than $1 for their contribution to the site. A good percentage of it is likely spam, but it still shows that, for most new users, Steemit is far from profitable. I’m afraid that if it is to grow exponentially, so will this issue, driving potential new users to other, more lucrative, alternatives.
Platforms like Akasha and Yours will soon be competing with Steemit. They're likely going to be more than 60k users behind it at their launch, but they'll catch up quickly if newcomers realize they have more influence over there. That influence could be drastically transformed by reducing inflated payouts.
The proposed solution
I hope the above remarks have convinced you that changes are needed. It should be mentioned that considerable progress has already been made aimed at solving some of these issues. For example, the recent modifications to the payout delay have been successful in reducing the average time a post stays on the trending page. This still only addresses part of the problem. After taking time a reading a post, curators currently have two choices to influence the payout of an article: upvoting, if content is worth more than the estimated payout, or flagging, for spam or dishonest content. But that leaves a place for a third option: one that would reduce the payout when it’s inflated, independent on the voter’s liking or disliking of the content.
A user’s choice to upvote or downvote an article should be based on its content, in addition to what they believe its value to be compared to the estimated payout. The option to flag should remain as a mean to decrease someone’s reputation and prevent spamming or dishonest content.
This might all sound like a stretch, and maybe you’re not aware of the influence that downvoting can have, but some downvoting whale action has already been happening. See @smooth’s comment on this announcement post:
To be clear, I’m not merely suggesting here that downvotes should be used to discourage bad content, but rather advocating the use of downvotes on good content that may have an inflated reward.
There’s nothing inherently bad with promoting an upvote only culture on a platform of complete information, but the problem is just that: the medium we use to access that information favors certain posts, namely, those that were heavily upvoted early after their creation.
In a context in which an important disparity exists in exposure to different blogs, users shouldn’t simply upvote what they find interesting, they should vote in a way that brings the payout closer to what they deem to be the real value of a certain post. As such, increased exposure would equate to a fairer payout, as opposed to an inflated one as discussed above.
The problem with simply adding a downvote button is that it’ll have little use if it isn’t incentivized in the same way that upvoting is. An ideal system would incentivize both positive and negative votes, so long as their net effect is to pay the content creator a fair price for their contribution. The question then becomes: in which situations should downvotes be rewarded?
Assuming a free market of positive and negative votes: the more people partake in the curation process, the more representative it is of its quality. Going by this, we refer to the fair value of a given post by its payout after the first (12h) or second delay (30 days) depending on the period in which voting takes place. The curation rewards would then be attributed to those who correctly predicted the final payout by voting accordingly. Here’s an example:
@dan posts an update, announcing a new feature on Steemit.com. Browsing through the “new” section, @wingz upvotes only a few minutes after the creation of the post when it’s still at $9.40, expecting it to go higher. A few hours later, @ned wakes up and looks at the top trending posts. It’s a nice, sunny day and he sees @dan’s post at $6,245.33. Feeling generous, he upvotes his partner’s article. Finally, @smooth finds the post at $7,129.21. He evaluates that its current payout estimate is higher than its fair value, so he downvotes it. 12 hours after its creation, the payout (fair value) settles at $4,124.33.
Here, @wingz and @smooth stand to receive a curation reward for correctly assessing the fair value of the post. On the other hand, @ned would receive no reward for upvoting purely based on his mood and the author’s name, not considering the actual content quality.
For the proposition described above to be implemented, no major changes in the weighting system would be necessary. Only the estimated payout before (EPB) and after (EPA) a vote would need to be recorded. The current rules for calculating curation rewards (based on weights) can be summarized as the following:
- Curation rewards scale with VESTS (similar to SP, see the conversion ratio)
- Rewards scale with voting power, which decreases after each upvote before slowly growing back towards 100%
- Curation rewards scale with the weight given to your vote if it is greater than 0 (0 to 100%) - No reward is given for a negative weight (downvote).
- Given 2 users with the same amount of Steem Power, the earlier one appears on the voting list (ordered by time of vote), the larger their reward will be.
- Votes casted
tminutes after the creation of a post where
t<30 minuteswill have their rewards reduced by
EPB and EPA would come into play in situations where the fair value lies between the two. In those cases, the voter’s share of the curation rewards could be adjusted according to their proportional contribution in correctly valuing content. The reward per vote would then be given out according to those relations:
This type of payout structure would have the additional advantage of rapidly counterbalancing the effect of bots that upvote users uniquely based on the payout received for their past content. Curators who read the post could better assess value and benefit from downvoting a horde of bots that inflated a payout past its fair value.
While this doesn’t directly address problems due to visibility, I believe it would help in 2 ways. First, an adjustment in prices on the trending page would automatically grant more relative curating power to those who do not participate in inflating payouts. A price distribution that reflects the comparatively narrow range of content quality would allow for small price variations to change the ranking order of a post significantly. Secondly, posts that suffer from low visibility would have their curation rewards increased by redistribution of money that is currently being given to more visible posts for no valid reason.
I’m sure that lots of thought has been put behind the economics of Steem by its creators. I hope I was successful in highlighting the current issues on the platform and showing how an incentivized downvoting system could make the situation better. Steem is still in beta and I think it’s important for the community to challenge established ideas if other alternatives could improve the overall user experience.
Please let me know me know what you think about any of the points raised by replying below.