Facebook Demotes Posts That Use Engagement Bait

As part of a broader battle against spammers and other system gamers, Facebook is cracking down on the solicitation of “likes,” shares, and other types of virtual engagement.

It’s what Facebook calls “engagement bait,” or the manipulation of its News Feed algorithm in order to boost engagement and, thus, achieve greater reach.

“Starting this week, we will begin demoting individual posts from people and Pages that use engagement bait,” Henry Silverman and Lin Huang, operations integrity specialist and an engineer at Facebook, note in a new blog post.

“Publishers and other businesses that use engagement bait tactics in their posts should expect their reach on these posts to decrease,” Silverman and Huang warn. “Pages that repeatedly share engagement bait posts will see more significant drops in reach.”



For Facebook, the change is part of a wider effort to foster more authentic engagement on its platform.

That effort includes tasking teams with reviewing and categorized hundreds of thousands of posts, which guide a machine learning model in order to detect different types of engagement bait.

Over the coming weeks, Facebook will also begin implementing stricter demotions for Pages that systematically and repeatedly use engagement bait to artificially gain reach in News Feed.

“We will roll out this Page-level demotion over the course of several weeks to give publishers time to adapt and avoid inadvertently using engagement bait in their posts,” according to Silverman and Huang.

Facebook will do its best not to demote posts that ask people for help, advice or recommendations, such as circulating a missing child report, raising money for a cause or asking for travel tips.

Rather, it plans to demote posts that go against one of its key News Feed values: “authenticity.”

The ultimate goal is to reduce the spread of content that is spammy, sensational or misleading in order to promote more meaningful and authentic conversations on Facebook, according to Silverman and Huang.

Next story loading loading..