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.
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
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.
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
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.
So how much does one of these Average Person make per post in these 4 categories?
This is the average value. How does the median look like?
We will now divide the data into 4 groups based on the first tag.
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.
Next we will examine the Average values per week in each category and compare how much each author made in aggregate and per post
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
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?
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.
