The idea of a suggestion feed is to pull in contents from real people instead of machines. However, it has a chicken or an egg problem. When there are a few users, the feed would remain empty. So it needs to prepopulate it initially with existing contents.
The solution was to add RSS feed and treat publishers like another account.
This week I added 14 publishers: Popular Science, Science Magazine, AEON, Forbes, Vice, Vox, Nature, National Geographic, Literature Hub, The Paris Review, Vox, Artnews, Artspace, Frieze, and Artsy. They were selected on the basis of the length of each article. Since the feed suggestion is based on articles you read and the aim is to learn deeper, I omitted news like contents. Those 14 would be added on top of the existing 12 publishers so it would have a total of 26 publishers.
I was working on adding bot publishers. If there were more contents to give, the algorithm works much better. The concept came from Deep Learning where the algorithm was not changed but the amount of data available at hand made the difference. The focus was on adding longer articles. Longreads so to say. On top, I picked the topics around science, literature, and art since they were the primary interests of the existing users. I want to give the best suggestions for a few users and wait for their feedback. The idea of reading in the tracked platform makes sense, but there are so many places you can consume contents, I ‘m still skeptical if this idea would be validated. The feedback will be to come in a week or two.