Comment by passion__desire
2 years ago
One feature I would like for an Recommender Systems to have is : explicit ability to jump in and out of filter bubbles or research rabbit holes. Another example would be, put yourself in the shoes of another, e.g. what content is liked by game developers generally. apart from general gamedev content, what do they like, where do they take inspiration from, etc.
I remember there was a project built on instagram which allowed a person to view instagram as it looked like to a particular celebrity.
I'm a bit divided on this feature. On one hand, I would like to have this feature; it would be awesome to see the recommendation of people from different jobs. On the other hand, I'm a bit concerned about privacy. The system must ensure that each group is big enough to avoid the leak of someone's recommendations. I don't want anyone to know exactly what I'm liking and what I'm watching.
If I recall correctly, myCANAL (the French Netflix) used to have a similar feature. You could access the recommendations of personalities of the channel, but it was curated manually.