Introduction

In this analysis, we were asked to examine the most important feature of one of the NIR network projects At first, I went to the top projects of the network The criterion of this superiority was the number of transactions. Then I went to check this project To check, I have used different criteria, which I will refer to each one during the analysis But before starting, it is better to have a look at the definition of the project that I have chosen, that is, near crowd

what is NEAR Crowd

based on NEAR Crowd site

NEAR Crowd is a service that allows people earn NEAR by completing small tasks. \n \n While tasks are provided and funded by a centralized entity, called the Requestor, NEAR Crowd significantly limits the power that the Requestor has, and moves the power to the community instead. In particular, while the Requestor provides the specification of what needs to be done in each task, it's the community that decides whether each task is completed correctly according to this specification. This is achieved by creating a set of rules, checks and balances that are enforced by a smart contract deployed on NEAR. \n \n

How it works

Basics

We will explore how NEAR Crowd works with a simple example. \n \n The Requestor wants to transcribe short audio clips, and submits 100 of them to the contract, along with the sufficient funds to cover the work. Five participants: Alice, Bob, Carol, Daryl and Eve, apply to perform the transcriptions. \n \n Alice applies for a task first, and receives one of the audio clips. She then transcribes it, and submits the transcription. Bob applies for the task following Alice's submission. \n \n Since there are some tasks that were completed, but were not yet reviewed, Bob has a chance to either receive a new clip to be transcribed, or one of the already transcribed clips for a review. Bob indeed receives Alice's clip for review. He listens to the clip, confirms that the transcription is correct, and accepts it. Once it is accepted, both Alice and Bob receive credit for it. \n \n

First, the top 5 projects in the network can be seen in the pie chart The percentages written in the chart show the percentages of these projects about each other (not about all projects). It can be seen that NEAR Crowd and Aurora have almost the same transaction percentage. Then, for further investigation, it was necessary to consider the date of the first transaction in the network for project NEAR Crowd. It should be noted that all analyzes have been done since this date. Then we will briefly compare the first two projects. The interesting thing about both of them is that NEAR Crowd has recorded fewer transaction fees despite having more transactions. This happened to the transactions of this project probably due to many transactions but with low fees.

Part one

general information

Part Two

transaction

Part Three

users

Part Four

conclusion

In this analysis, I tried to investigate the most important features of a project First, I examined the number of transactions, which showed the amount of use of the project, as it is clear that the amount of use of this project has decreased in recent months. Then I checked the users, and like the transactions, the number of users has decreased a bit Another important point was the strange site of the project. This site had very good UI and UX and it is better to spend more capital and energy on the site in the future for the growth of the project, and in the next Altseason, we can be very hopeful for the growth of this project.

What impact is this project having on NEAR?

NEAR Crowd is considered one of the most important projects of the network and has definitely been influential As it is clear from the graph above, with the decrease in the number of users and the number of network transactions, the overall transaction graph has also been decreasing. Also, this relationship is a two-way relationship, just as the network is important for the project, the project is also important for the network

Sources

awesomenear.com/near-crowd

nearcrowd.com

github.com/NEARCrowd

In the next two parts I will analyze the number of transactions and then users First, it can be seen that after May 25th, no other day has recorded a higher than the average number of transactions. So this means that the number of transactions in the project has decreased in recent months. But in the last month, the number of transactions has increased and is closer to the average line In the circular diagram of the number of labels, it can be seen that about half of the transactions were of the type claim_assignment

in this part At first, the number of single users can be seen separately every day It can be seen that, like the number of transactions, the number of users has been decreasing in recent months And this issue will be one of the problems of crypto winter Since May, almost no day has had more than 1500 active users. The most important users who have interacted with NEAR Crowd are the following three users respectively

• ralfusha
• uchastok
• kudri18

And also in the last graph, you can see the growth rate of users