Some people actively desire this kind of algorithm because they find it easier to find content they like this way.
Raw chronological order tends to overweight the frequent posters. If you follow someone who posts 10 times a day, and 99 people who post once a week, your feed will be dominated by 1% of the users representing 40% of the posts you see.
One simple algorithm that is almost always better for user experiences is to retrieve the most recent X posts from each of the followed accounts and then sort that by chronological order. Once you’re doing that, though, you’re probably thinking about ways to optimize the experience in other ways. What should the value of X be? Do you want to hide posts the user has already seen, unless there’s been a lot of comment/followup activity? Do you want to prioritize posts in which the user was specifically tagged in a comment? Or the post itself? If so, how much?
It’s a non-trivial problem that would require thoughtful design, even for a zero advertising, zero profit motive service.
Letting the user decide? If the user decided that they liked fly fishing 8 stars and mother-in-law 0 stars, then the algorithm would show mother-in-law once a week at best and fly fishing 8x out of 10 posts.
Yeah, you’re describing an algorithm that incorporates data about the user’s previous likes. I’m saying that any decent user experience will include prioritization and weight of different posts, on a user by user basis, so the provider has no choice but to put together a ranking/recommendation algorithm that does more than simply sorts all available elements in chronological order.
If we had one public social media platform that would be the best way. It would force people to filter and learn how to interact with technology. But in our world people are lazy and a platform that picks the best value of X automatically for the most people will win. Even if it’s not actually how people want to see things.
Raw chronological order tends to overweight the frequent posters. If you follow someone who posts 10 times a day, and 99 people who post once a week, your feed will be dominated by 1% of the users representing 40% of the posts you see.
One simple algorithm that is almost always better for user experiences is to retrieve the most recent X posts from each of the followed accounts and then sort that by chronological order. Once you’re doing that, though, you’re probably thinking about ways to optimize the experience in other ways. What should the value of X be? Do you want to hide posts the user has already seen, unless there’s been a lot of comment/followup activity? Do you want to prioritize posts in which the user was specifically tagged in a comment? Or the post itself? If so, how much?
It’s a non-trivial problem that would require thoughtful design, even for a zero advertising, zero profit motive service.
Letting the user decide? If the user decided that they liked fly fishing 8 stars and mother-in-law 0 stars, then the algorithm would show mother-in-law once a week at best and fly fishing 8x out of 10 posts.
Yeah, you’re describing an algorithm that incorporates data about the user’s previous likes. I’m saying that any decent user experience will include prioritization and weight of different posts, on a user by user basis, so the provider has no choice but to put together a ranking/recommendation algorithm that does more than simply sorts all available elements in chronological order.
If we had one public social media platform that would be the best way. It would force people to filter and learn how to interact with technology. But in our world people are lazy and a platform that picks the best value of X automatically for the most people will win. Even if it’s not actually how people want to see things.
Losing content of one poster and getting double content of others isn’t a solution though.