14 Sep
Facebook’s Subscribe Button to Come With Personalized “Suggested User” Subscription Recommendations
Posted by Josh Constine, under Facebook, Subscribe[Update: The "People to Subscribe to" sidebar module is now live. It displays subscription suggestions along with friends who've subscribed to someone, or where the suggested user works.]
These personalized recommendations contrast with Twitter’s original king-making “Suggested User” list that provided new registrants with recommendations of people to follow from a limited list. That feature was criticized for causing certain celebrities and friends of Twitter employees to rapidly gain tens of thousands of followers. Instead, Facebook’s subscription recommendations will promote authors who publish updates especially relevant to a user and their network.
As the Subscribe feature just launched, most users currently have no subscriptions or subscribers. However, once some of a user’s friends have organically discovered authors to Subscribe to, Facebook will begin asking users if they also want to follow those authors.
Facebook does have some features in place to assist with subscription discovery. Activity stories are posted on a user’s wall and to the news feeds of their friends when they Subscribe to new people. This provides viral exposure for those receiving subscriptions.
When users visit the profile on a non-friend, they’ll see if any of their friends have subscribed to that person. This information appears in the friendship panel on the right side of the profile that usually displays mutual friends Likes.
Users can also visit Subscriptions and Subscribers tabs in the profile’s left navigation menu. If a user has a friend who’s opinion that trust, they could go through the Subscriptions tab and begin following all the people that friend has subscribed to.
Facebook is using the fact that assymetrical following isn’t its primary feature to help it improve on Twitter’s blunder. Most users will have forged friendships before they start subscribing to people, giving Facebook the data necessary to power a personalized subscription recommendation engine rather than blindly suggesting the same authors to everyone.
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