Which topics in Steemit receive the highest reward?

I have been looking at the posts that trends over the past few weeks and wrote a post on how the diversity of the posts are increasing, which are indeed a very good thing for Steemit. You can read the post here

Today I decided to have a look at which topics have the highest payouts.

In the above example it is clear that the Steemit tag is used a lot by the auhors in their posts. I think it come naturally to use this tag in most posts. The second topic that received high payouts is the @introduceyourself tag. Again very predictable due to the fact that the platform was recently launched. An interesting trend is that is clear in the past week or so is that this tag is now being used less frequently, or actually less of the posts trend.

My brother @clayboy recently registered as a user and did not have much success in her first post. His second post actually received a higher payout than the first. The post can be viewed here. In my book the book on #introduceyourself are closed. I think it is very important for users to be verified with images to ensure we do not have scams etc. My point is that I do not believe as many #introduceyourself will trend than in the past.

When we remove the #steemit and #introduceyourself from the graph , it gives us a much better spread. I only focussed on the Top 40 Paid out posts.

The top 5 leading topics are Photography, Life, Travel, Money and Crypto-News. These topics are clearly leading the way as all of these posts had more than 80 000 SBD paid out over the past few weeks to active steemit users. Photography is touching on 150 000 SBD.

I think #marijuana at number 6 is a surprise contender this high up. I do however believe that @berniesanders voting on this subject, definitely have something to do with it.

Writing, News, Philosophy and Food also made the top 10 list.

In total payouts were made to a diverse 90 topics with $0,06 for the topic of #plastic .
I will give it a few weeks and do the same exercise. Let's see how the graph is affected through time.

The information provided is available on https://steemit.com/tags.html/trending