Repository:

https://github.com/Steemhunt/web

Introduction

The Steemhunt project have made a great progress in Q1 2019. They have made a very successful IEO (Initial Exchange Offering), through a various exchange, raising funds for the project. Doing this, they have proven that the project has a great value and it is been appreciated by investors. They are the first to do something like this from all the projects on the Steem blockchain, paving the way for others to follow.

They have a solid road map ahead with two new platforms set to launch, Reviewhunt and Ideahunt. It will be an interesting year to follow their development. A bull run in the crypto prices will give even a bigger push to the project. Since they are a project for discovering cool new products, a lot of new crypto projects can use the platform.

Scope of Analysis

In this analysis, daily data will be presented for the Steemhunt activities. Steemhunt has a unique way of operating with hunts being posted and then approved by the moderators. They are rewarding the top hunt for the day with a vote from them. Furthermore, they are rewarding comments on the hunts. It is not just about finding a cool new product, but engaging discussion as well. Because of these a more detailed look will be made on the comments side and on the Steemhunt moderators. A ranking on the Steemhunt users for 2019 will be made as well.

The analysis was carried out for the period from 01.01.2019 to 31.03.2019. Data from the STEEM blockchain was used and details of the queries can be found at the bottom of this post. Previous analysis for 2018 can be found on this post.

Activity on Steemhunt

Activity on the platform is in posts and comments. Steemhunt have their own web interface and web extension as well. All the posts and comments made on the Steemhunt web are ending on the Steem blockchain. They have integrated a scoring system for the products that appears on their interface, so they can make daily ranks of the products.

Posts and comments can be made on their web, but also from the other Steem interfaces like Steemit, Partiko, Busy etc. Because of this I have approached the data activities in two different ways. The first is showing all the post and comments with the steemhunt tag, and the second is for the posts and comment made only with the steemhunt.app.

Here is the data for Q1 2019. Data for each day was collected and presented on this graph.

The upper line represents the number of posts and comments with the steemhunt tag and the lower one the number of posts and comments made only with the steemhunt.app.

As expected, the overall data containing the steemhunt tag have more activities that the posts and comments made only trough the Steemhunt interface.

The total number of posts and comments on Steemhunt in 2019 is 90.090, out of which 80.871 posted from the Steemhunt web.

This is a difference just above 10%. It is not a big difference meaning the Steemhunt web is being used a lot. Since this is an analysis about the @steemhunt, in the next charts only the data from the Steemhunt web will be presented and analysed.

The overall activity in the period analysed is very stable. Almost a constant number of activities with just a bit of slight increase. The average posts and comments per day is around 900. We can tell that Steemhunt have build a solid user base. Hope to see growth in the next period with all the positive moves they have made.

Posts and Comments Breakdown

As already mentioned, Steemhunt is stimulating commenting on the platform. Let’s see the structure of posts and comments on Steemhunt in Q1 2019.

Below is a breakdown of posts and comments and their movement in Q1 2019.

The upper line represents the comments. Immediately we can see that there are a lot more comments then posts on the platform. Steemhunt wants user’s engagement and comments. They want to hear what people think about the products posted there. And they have pretty much succeeded in their mission.

A total of 16.985 posts on the platform, and 63.886 comments.
A 1 to 4 ratio post to comments.

The activities follow the first chart, with a constant number of posts and comments. The average number of posts per day is around 180 and the average number of comments per day is 710.

Comments Breakdown

Users get rewarded for a decent comment on the platform, and because of this, a lot of comments are produced on the Steemhunt platform. Let’s get a closer look to the comments.

Comments are made from Steemhunt users, moderators and the Steemhunt account as well. The moderators approve each hunt with a comment. Steemhunt is commenting when they vote a hunt.

Here is a breakdown of comments from users, moderators and the @steemhunt account.

The upper line represents comments from users, the middle one moderators comments, and the lower one steemhunt comments.

A total of 36.792 user comments, 18.157 moderators comments and a 8.937 Steemhunt comments.

That is a lot of comments 😊. The users share is around 58%. The moderators have done an excellent job as well with 18k of comments. Bravo to them.

Moderatos Activities on Steemhunt in Q1 2019

Since moderators are playing such an important role on the Steemhunt platform, approving each hunt, lets take a look at their activities on the platform. More closely on the number of comments they posted, because in this manner they approve the hunts.

The Steemhunt moderators team is: @teamhumble8684, @fknmayhem, @dayleeo, @urbangladiator, @bitrocker2020, @joannewong, @monajam, @pialejoana, @geekgirl, and @playitforward.

The champion for the Q1 2019 is @teamhumble with more than 3000 comments. Close to him is @monajam, and third is @pialejoana. @monajam is interesting.

Here is a chart on the number of comments from moderators, cumulative per day.

Looks like all of them are also constant in the number of daily comments with no significant changes in the period. All the lines are almost linear. @playitforward seems to have a break in the period analysed 😊.

Steemhunt Votes in Q1 2019

Steemhunt reward its users with votes for the product they hunt and put them on the platform. Also, they reward users for the comments they made. The highest the hunt score the better the vote. The comments are also voted based on the hunt score.

Here how the voting looks in Q1 2019.

The total number of posts and comments voted from Steemhunt in Q1 2019 was 42.123

A great number of votes! Steemhunt has gave a great support to community with this number of votes. This is showing that they are on of the most supportive dApp on the Steem blockchain.

From the chart we can see that the number of votes follows the trend in activites in the period analysed. It is almost constant with a very slight increase. The average number of daily votes from Steemhunt is 480.

Number of Monthly Users Voted

Below is a chart with the number of monthly users that received vote from Steemhunt.

In Q1 2019 the number of monthly users supported from Steemhunt is around 300. The number of users have also stabilzed itself after the drop in 2018.

Top Steemhunt Users in Q1 2019

Below is a table with the most active Steemhunt users ranked by the number of posts and comments they made.

No	User	Number of posts and comments
1	@rem-steem	1425
2	@vinzie1	857
3	@macoolette	683
4	@karamyog	636
5	@rabeel	629
6	@amar15	616
7	@kamchore	584
8	@rehan12	561
9	@mawahab	548
10	@focusnow	537

Congratulation to the top Steemhunt Users in Q1 2019! You have done a great job on the platform and been quite active.
An absolute champion in this period is @rem-steem with a total of 1425 posts and comments, second is @vinzie1, and on the third place @macoolette.
Note on the top users: The moderators are excluded from this ranking.

Conclusion

Steemhunt seems to enter a period of stabilization, after the overall drop in 2018. In Q1 2019 we can see a constant number of activities, users and votes. Moderators are doing their job with a great number of hunts approved.

An almost 17k hunts were made in this period and 64k of comments on them, from a total of 1241 author. Steemhunt casted a 42k votes to 403 authors.

Tools and Scripts

The data was gathered in Excel From Steemsql held and managed by @arcange.

The query used to get post information from the steemhunt web was:

SELECT
 author,
 total_payout_value,
 net_votes,
 created,
children,
category,
depth
FROM comments (NOLOCK)
 where CONVERT(DATE,created) BETWEEN '2019-01-01' AND '2019-03-31' AND
  IIF(isjson(comments.json_metadata) = 1, IIF(CHARINDEX('/', json_value(comments.json_metadata, '$.app')) > 0, SUBSTRING(json_value(comments.json_metadata, '$.app'), 1, CHARINDEX('/', json_value(comments.json_metadata, '$.app'))-1),json_value(comments.json_metadata, '$.app')), null) = 'steemhunt' 

The query used to get post information with the tag steemhunt was:

SELECT
    author,
json_metadata,
 permlink,
      total_payout_value,
    pending_payout_value,
    net_votes,
    created,
    children,
    Category,
    Depth

FROM comments (NOLOCK)
where CONVERT(DATE,created) BETWEEN '2019-01-01' AND '2019-03-31' and
contains (json_metadata, 'steemhunt') 

The query used to get vote information was:

SELECT    
voter,
author,
weight,
timestamp
 FROM Txvotes (NOLOCK)
 WHERE [voter] in ('steemhunt')
 AND CONVERT(DATE,timestamp) BETWEEN '2019-01-01' AND '2019-03-31' 

GitHub Account
https://github.com/dalz

All the best
@dalz