JAKARTA - Facebook revealed a number of ways to identify the user's willingness, one of which is by utilizing machine learning (ML). This technology is combined with a predictor in guessing the things that users of the platform like.
Launching from the official Facebook website, the company processes trillions of posts to be displayed to more than 2 billion users. Facebook builds a number of posts and thousands of signals in sorting out the posts according to its users.
The company says that when a user enters Facebook, the selection process immediately occurs behind the scenes. The process only takes a few seconds to display the post feed.
Once all that is done, a number of layers of the ML model and algorithm system immediately apply the method of guessing relevant and meaningful content to its users.
When the user passes certain steps, the algorithm system automatically reduces the number of candidate feeds from thousands to just a few hundred. This narrowed feed is then visible in the user's News Feed at any given moment.
In other words, the system will select and determine the posts that will appear in the user's News Feed. The system sorts the posts that users like the most.
A number of factors to detect user interest are user followers, what users follow, posts liked, and interactions among users. The system will infer user interests and display posts that are relevant to their interests.
Facebook provides the following examples:
Since Juan logged in yesterday, his friend Wei has posted photos of his spaniel rooster. Another friend, Saanvi, posts a video of her morning run. Her favorite page publishes interesting articles on the best way to see the Milky Way at night, while her favorite Cooking Group posts four new recipes.
"All of this content is considered relevant or interesting to Juan because he chooses to follow the person or Page who shared the article," wrote Facebook on its official blog.
The system evaluates posts through certain criteria, one of which is the suitability of the post to the user which allows further interaction with other users.
The system manages a lot of data, including narrowing posts, sorting out interests, relevance of posts, and so on. Therefore, Facebook uses a parallel post reader machine called Predictors.
Predictor is a smart machine that can combine and narrow posts to around 500 posts out of thousands. Facebook also presents a variety of content according to user interests. This whole process only takes a matter of seconds.
The system also provides a ranking for a number of posts that match the interests of its users. Which posts will appear in the news feed or News Feed.
Not only that, Facebook also revealed other factors to predict user interest.
“But liking (posts) isn't the only way people express their preferences on Facebook. Every day, people share articles they find interesting, watch videos of people or celebrities they follow, or leave thoughtful comments on their friends' posts. "
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