Some people tend to believe that experience is the greatest teacher but, experience itself is not only limited in many areas, it is also a very expensive lesson. This is why, 'learning from others mistakes' is an adage that has persisted through the ages.
Practice does not make perfect. Only perfect practice makes perfect. -Vince Lombardi
Practice is replicating a learning environment to mimic a reality in the hope that the skills learned in relative safety (low cost) will transfer through to where they will be needed in a particular situation. The problem is of course that the practice has a cost that many don't want to pay and, the quality of performance in a training area is limited as there is not necessarily the same drive as the real world would offer.
In Neuro-linguistic programming (NLP) there is an idea of modelling which is essentially the process of attempting to make practice perfect by observing and dissecting the processes of brilliance. I am not some NLP practitioner but, I was thinking about this today in regards to my post on User Authority (@steem-ua) and then later on @paulag's post on a contribution score that looks at engagement she is working on.
One of the things in my post I identified as a possible area of opportunity is that while the algorithms give a heavy multiplying factor to witness accounts, it would be more practical for the average user to filter them out. User Authority is essentially about building trust of an account through trusting the decisions of other trusted accounts to follow that account. Yes, it is more complicated than that I am sure but, it is enough for now.
So, in the top 100 of the User Authority list at the moment, (which is all that can be seen) there are many witness accounts but, that isn't necessarily helpful for a user to understand what is a good approach to behaving on Steem. Even though people keep talking about the code, it is the behavior of the people that really matters but, where do they get an example of accounts that exhibit behaviors that might lead them to where they want to be?
@paulag's working is trying to gauge the engagement of an account by looking at the transactions in and out. A highly engaged account likely has a lot of things like comments and votes coming in and, a lot going out. It is a balance sheet or exchange of sorts. In the past I have talked about community hubs being important for many reasons including a lead by example position. I have thought a fair bit about my own approach and I think I am pretty engaged here in various ways as well as potentially, a hub of some kind or another.
My UA score is 6.074 and I have a UA rank of 261 on platform. From my understanding, based on my followers, I am somewhat trusted. What I am wondering is what happens if my UA score is combined with an engagement score in some way? What would it show? Would I rise in the ranking or, fall?
I mentioned to @paulag that what would be interesting is to cherrypick accounts that represent various groups and model them visually to see points of overlap, similarities and of course, disparities. In this way, it would be possible to create a filter that would be able to identify and include a community node with high engagement from a resteem service. That is obviously pretty easy to see normally however an interface could use a tool like this to give a much better experience for its users or, at least the option for a much better experience.
However, what is more important perhaps is that these can create models of behavior patterns that will indicate other factors too such as work volumes required, behaviours, content types, earning potentials and, value added to the blockchain. Overlaid with other factors such as User Authority, it may uncover some very interesting behaviours of some very high earning accounts and, give a set of guidelines to a new account on what is required of them to reach various positions.
Even though there is actually no such thing as a perfect model, it would give much more concrete traits for accounts to follow and more sensitive tools for identifying accounts that are valuable or harmful to the community. Rather than relying on the nonsense Steem schools and random posts by strangers about "how to be successful on Steem", there would be concrete examples of what works and what doesn't.
On top of this and since this is the blockchain, an account could be modeled over time to see how it has behaved since account creation. For example, the growth of an organic account could be tracked against one that uses bidbots, the differences between commenting or not or, it can be visualized how a particular account behaves through price variance. It would be incredibly useful for any number of things to have this kind of tool at the disposal of developers at the very least.
It would be able to create a best practice guide for newcomers but, it would also be able to visualize how things like changes to the code or the environment effect behavior across account types.
Having ranking tools like UA combined with modelling tools that can look at engagement and interaction means that we would be able to really understand how the platform is working. At the moment, all the data is there it just isn't easy to use therefore impractical for most users.
With the right tools especially surrounding engagement, there is the potential to really understand the social aspect and inner working of the platform. It should be able to give strong indicators to which accounts are adding value and behaving in a community minded manner and, which are not. I would predict that an overlay of real engagement against the UA score would uncover some interesting relationships between accounts, both in the positive and negative.
I am not technically minded or skilled but from my understanding, Hivemind brings additional tools to make it easier to scrape data so potentially, the views that we have available to us of the blockchain will change. People talk about good engagement, community users and various circlejerks but it is mostly hearsay and rumour, very little concrete to back it up. A few half decent filters and it could all be laid bare. Some may rise in standing, some may fall as a deeper level of transparency is available.
I wonder if having a deeper view of interaction would be like social contracts and behavior will change for the better and solve some of the problems we currently face. Once we see ourselves against others, will we learn from their mistakes, or our own? It is all very interesting to ponder over.
Taraz [ a Steem original ]