Deep Dive of Steemit Tags

Choosing tags is often a last minute after thought but well chosen tags can give your post increased visibility.

Today I will examine 4 popular tags and look at some of the relationships to post payouts.

---

Steemit Tags

On Steemit you can use up to 5 tags, they can be any word you choose but people expect them to be some way related to your post. Using tags just because they get high payouts may lead to flags or downvotes if your content is not related to the tag.
For example the introduceyourself tag has been a place where new users would post an intro and often would get big upvotes from Whales as a kickstart on Steemit. People have been abusing this tag by posting multiple intro posts or just tagging it with the hope that a completely unrelated post would get an upvote.

Today I am going to examine 4 popular tags:
Photogrpahy, Art, Photo, introduceyourself

Overview

The aim here is to identify variables that lead to higher post payouts on these 4 tags for newer users, as well as trends in payouts for these tags since December.

Before digging into different relationships we will begin by looking at some aggregate figures for these tags.

Categories

There can be some overlap between the tags which I will not analyse in detail in this post. For the following analysis each grouping will be based on the first tag of the post only.
This is the most visible tag on a post as it appears as the category and gets added to the permalink of the post and is likely to be the main tag used by newer users.
e.g. if photography was the second tag I would not be including the post

New users

For our analysis we wish examine the more regular experience for people on Steemit. People who have a lot of influence and have been here for a while are likely to have a higher Rep. For the rest of this analysis we restrict the data to people with Rep > 30 and < 50
The people posting on Steemit can be put into several different groups. There are people who have been on Steemit for a long time and may have achieved a lot of influence (as well as high Rep), and others who spam tags (probably have a low Rep).

The following graph shows the numbers per week for these 4 category tags since December.

• There was increased activity due to the SBD bonanza, increases in the price of Steem as well as many new users signing up to Steemit over this period.

Averages (per post)

So how much does one of these Average Person make per post in these 4 categories?

• Pretty impressive?, between 1 & 1.5 Dollars for some weeks!

This is the average value. How does the median look like?

• This feels more like the experience of the vast majority of Steemians.

We will now divide the data into 4 groups based on the first tag.

Payout Per Post Over time

Do spammers get diminishing returns?
The next graph shows the payouts on posts ordered by the number of posts made by each author in this period.
i.e. If an author made several posts, the payout on the first post would be at position 1, the payout on the second post at 2 and so on.

You may expect spammers that create a lot of posts to get a diminishing return.

• The introduceyourself tag is one of the tags that people generally are advised not to spam. I am very surprised to see so many posts by some authors, up to 30!

• Payout on this tag seems to be greater for authors with a lower frequency of posting.

• There are smaller numbers on the art tag but again payout seems to be higher for posts where authors posted less. Maybe an indication of quality?

Average Values in Each Category

Next we will examine the Average values per week in each category and compare how much each author made in aggregate and per post

---

Correlations

It can sometimes feel like payouts on posts are random.
Is there any correlation between the variables such as number of votes, comments etc to payout?

Blue represents a high Pearson Correlation and red a low correlation

Number of Comments seems to be the highest level of correlation but event that is a very low statstically

Payouts Per Author

What if instead of looking at posts if we group the data by Author to see is there a correlation to aggregate payout to author features?

Correlations

Conclusion

There does not appear to be a strong correlation between any of the factors we looked at and the post payouts for this group of authors.

The first few posts by authors in these categories got higher rewards but there is diminishing return after that. It's likely that authors are moving on to other tags, or not using these 4 as the first tag after an initial period.

Does this analysis reflect your experience with using these tags?

---

Thank you for reading this. I write on Steemit about Blockchain, Cryptocurrency, Travel and lots of random topics.