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Thanks @lemouth. There really is a wealth of data available from steemit. It's a very rich datasource. In the coming weeks I am going to try out some machine learning techniques to see what I can uncover.

I remember having programmed a few python scripts in the past (if interested, it is here). It is indeed possible to get a lot of stats from the database.

This being said, stats for comment would be great too, at this moment where the comments can get significant rewards again.

That's a very interesting post. I'll I may borrow some of your analysis in my approach. It's an interesting way to look at how successful a topic or feature is. Great post.

I also want to incorporate curation rewards, voting, views and comments into my analysis. It takes a bit of work to parse the data and clean it but i have a good base of code built up now so I am getting there. The next thing I want to tackle is sentiment analysis on the text body in posts. Who are the happy posters and how do they do in terms of rewards :)

That's a very interesting program (in both way of the words :p )! I would have loved to help you, but I have unfortunately very little time (and I prefer to concentrate on posting on science topics ;) )

Thanks for the very nice comment btw :)

No worries, you contribute with your support and comments. Thanks again.

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