I suspect this is less accurate at recommending personalized content compared social media algorithms (like tiktok) that consider more data, yet is also not much more transparent than those algorithms.
You could show the actual eigenkarma—but you’d have to accurately convey what that number means, make sure that users don’t think it’s global like reddit/hn, and you can’t show it when logged, in link previews, nor in google search. Compare this to the simplicity of showing global karma—it’s just a number and 2 tiny buttons that can be inline with the text. LW jams two karmas in each comment and it makes sense. The anime search website Anilist lets users vote on category/genre tags and similar shows on each show’s page, and it all fits.
I think “stuff liked by writers who wrote stuff I like” is less accurate than “stuff liked by people who liked content I like”. There are usually much fewer writers than likers. I think it’s also less transparent than “stuff written by writers I subscribed to”
I suspect this is less accurate at recommending personalized content compared social media algorithms (like tiktok) that consider more data, yet is also not much more transparent than those algorithms.
You could show the actual eigenkarma—but you’d have to accurately convey what that number means, make sure that users don’t think it’s global like reddit/hn, and you can’t show it when logged, in link previews, nor in google search. Compare this to the simplicity of showing global karma—it’s just a number and 2 tiny buttons that can be inline with the text. LW jams two karmas in each comment and it makes sense. The anime search website Anilist lets users vote on category/genre tags and similar shows on each show’s page, and it all fits.
I think “stuff liked by writers who wrote stuff I like” is less accurate than “stuff liked by people who liked content I like”. There are usually much fewer writers than likers.
I think it’s also less transparent than “stuff written by writers I subscribed to”