Congratulations! Web2 social media platforms heavily use machine learning to show users content they might like. I am pleased that you are working in this direction at Hive. I think Veews will fill an essential gap for Hive.
The current trending algorithm prioritizes content based on the monetary value of the votes they receive. On the other hand, how many people read the content is also important. We can see the number of views on Peakd. It may be helpful to use both criteria together.
Interacting with a person results in being more curious about the content they produce. Therefore, I would like to see the content of my friends with whom I interact first.
The time spent on a page and whether scrolling down is done on that page can also give an idea about the content. Because I guess the like and dislike buttons will not be used much.
An algorithm that considers the tags of interest with the above criteria would have pleased me as a user.
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Yup, all in the plans. We want to make sure people see their friends stuff as well and do it in a way that they are always loving what they see.