Repository:
https://github.com/steemit/steem
Introduction
The last month was a month for dApps promotion on Steemit. We had interesting situation and a real community effort that put steem dApps on @stateofthedapps. Some of the persons behind this were @soyrosa and @therealwolf. Steem dApps are now on State of the dApps and can be compared how are they doing against the other crypto platform. And they are not bad at all. The Steemit interface is actually on the first place. @therealwolf also created a dedicated page for the steem dapps.
Watching how dApps are developing is pretty exciting. These are early times in the industry and everyone is experimenting. A lot of the prominent people in the industry have agreed that a real life crypto usage, will come from dApps.
I’m doing this analysis for a couple of months now. The results on the State of the dApps wasn’t that surprising. And if we look even closer the structure of the dApps on the other platform will see that most of them are gambling dApps. Steem have the most genuine dApps.
This said, let’s see the numbers.
Scope of Analysis
The analysis was carried out for the period from 20.11.2018 to 20.12.2018. Data from the STEEM blockchain was used and details of the queries can be found at the bottom of this post.
Activities on dApps
I’m starting this analysis with an overview of the activities on dApps (posts and comments). The past period was one of the worst for the crypto world. The value of Steem dropped a lot. On 14th November it was around 0,74$. Today it is around 0,27. That is almost 2/3 of the value lost, in a period of month and a half. This kind of drop cannot be without consequences. A drop in activities is expected as well.
Here are the number of posts and comments made on each dApp.
The only dApp that shows growth in activities, compared with the previous analysis is @partiko. Partiko is now firs on the list, taking the tron from @busy. All of the other dApp have dropped in activitie. The main reason for this, can be found because of the last month @partiko had a delegation round, and started to reward it users even more.
Next comes the alternative interface to Steemit, @busy and @esteem. The other dApps are also doing a great job.
Number of users voted from the dApps
One of the indexes that I personally find quite important is the number of users that the dApp support. Because of this, I’m putting this criteria. Here it is.
@partiko is the unmatched champion here with more than 2400 users voted for. It is leading by quite a lot. It is followed by @busy and @esteem. They are supporting more than 1000 users.
The interesting thing with @partiko is when I was doing the last month analysis they didn’t had a big amount of SP. They were on the bottom with SP. I was thinking wouldn’t be great for @partiko to gather some amount of SP. Look at the number of users they support. And just after a week or so, they announced their delegation plan. They planned to gather 100k SP but achieved 250k in just four days.
This shows that the community values a good product. And they build the product first, and asked for delegation later. Way to go.
From the other dApps @actifit is also growing and bringing more users and gives them support. The other dapps like @tasteem, @steemhunt, @dtube, @steepshot, @dlike and @utopian-io are also doing a great job and support quite a number of users.
Compering the dApps only by the number of users they support is important, but there are also other things to take into consideration. Every dApp have a different strategy to give their support to the community. Let’s take a look at some other aspects.
Number on posts and comments voted
Some of the other main thing about dApps is the activity they have on their platforms and the number of the posts and comments they vote on. Here are the number of posts and comments each dApp they have voted on.
@steem-ua comes first here, closely followed by @steemhunt. @steem-ua, or Steem User Authority is an alternative user reputation system to the current system that Steemit have. A lot of people complain about the current reputation system, arguing that it is broken. Steem-UA tries to fix that. They are doing ranking on the Steemit users and reward the delagators with votes according to their UA score and the score of the post.
Next comes @steemhunt. This score comes from the fact that @steemhunt rewards comments, and not just posts. Obviously, there are a lot commenting happening on Steemhunt 😊. I have personally used the platform and I can say it is a nice way to get reward just for a decent comment.
Average Votes Value by dApps
Except the number of users dApps support, and the number of posts and comment, another important parameter is the value of their vote. And this depends on the amount of SP they are holding.
Here is a representation of the SP that dApps are holding.
Different dApps use their SP in different manner. Some are rewarding more users, and some less. Here is how they distribute their voting power and the average vote per dApp.
Utopian is the leader here. There average vote is around 18$. They are supporting open source contributions. There are various of categories in which one can make contribution, like blog, analysis, developers, translation etc. After @utopian-io next comes @dtube. The Steemit video platform. Then comes @tasteem, a restaurant reviewing platform. We can see here that the vote value follows the amount of SP the DApps are holding.
The biggest distribution of votes is coming from @steemhunt. Compared to their SP.
The votes values are according to todays steem prices.
Summary
The web platforms that are following the dApps are making rankings on them with a custom algorithm that is giving weight to a specific criteria. Here I’m not doing this. The rankings are made above, according to different criteria. In the end are all the data that was used, and the dApps in alphabetic order. Here it is.
Steem Monster and Magic Dice
A word on this two. These are steem based games that are showing great activites recently. But the way they operate is not suitable to include them in this analysis.
@steemmonsters is and excellent project and it is ranked on second place just after Steemit itself. It deserve it and the team behind it is doing a great job.
Magic Dice is a game of luck 😊. You put your bet, roll the dice and hope for the best. Having in mind that this kind of dApps are the one with most users on other platforms, no wonder we are starting to see them here.
Conclusion
From all the project presented above we can see that at the moment the Steemit ecosystem provide support to its users in a variety of different ways. There is something for everyone, no doubt about that. Some of this project may still need a little bit refining.
In the bear market the overall acititie is down, except for @partiko who is showing growth.
But if one is willing to grow here on Steemit there is a lot of opportunity out there, from tracking his activity, reviewing restaurants or making contribution to the open source projects. Or just use a different Steemit interface.
Tools and Scripts
The data was gathered in Excel From Steemsql held and managed by @arcange.
@paulag queries are of great help as well. Many thanks to her.
The query used to get vote information was
Source = Sql.Database("vip.steemsql.com", "DBSteem", [Query="SELECT#(lf)*#(lf)FROM #(lf)Txvotes (NOLOCK)#(lf)#(lf)WHERE [voter] in ('actifit','busy.pay','dlike','dtube','esteemapp','partiko','steemhunt','steempress-io','tasteem','utopian-io','steempeak, steem-ua')#(lf)and CONVERT(DATE,timestamp) BETWEEN '2018-11-20' AND '2018-12-20'"]), #"Added Custom" = Table.AddColumn(Source, "% weight", each [weight]/10000), #"Changed Type" = Table.TransformColumnTypes(#"Added Custom",{{"% weight", Percentage.Type}}), #"Added Custom1" = Table.AddColumn(#"Changed Type", "Current vote worth", each 95.44), #"Added Custom2" = Table.AddColumn(#"Added Custom1", "approx vote $", each [Current vote worth]*[#"% weight"]), #"Changed Type1" = Table.TransformColumnTypes(#"Added Custom2",{{"timestamp", type date}, {"approx vote $", type number}})
The query used to get posts information was
Source = Sql.Database("vip.steemsql.com", "DBSteem", [Query="SELECT#(lf) author,#(lf)json_metadata,#(lf) permlink,#(lf) total_payout_value,#(lf) pending_payout_value,#(lf) net_votes,#(lf) created,#(lf) children,#(lf) Category,#(lf) Depth#(lf)#(lf)FROM comments (NOLOCK)#(lf)where CONVERT(DATE,created) BETWEEN '2018-11-20' AND '2018-12-20' and#(lf)contains (json_metadata, 'actifit')#(lf)#(lf)#(lf)#(lf)"]), #"Changed Type" = Table.TransformColumnTypes(Source,{{"created", type date}})
GitHub Account
https://github.com/dalz
All the best
@dalz