click me —

Facebook continues its war on clickbait

New system “identifies words and phrases that are commonly used in clickbait.”

Facebook thinks headlines need to sober up.
Facebook thinks headlines need to sober up.

In 2014, Facebook said it was going to take steps to favor clear headlines over so-called clickbait, which it defines as headlines that try to cultivate interest in a story by omitting key pieces of information, or by misrepresenting what’s in the actual post. Now, the social media giant has revised its clickbait-tackling scheme, which for the past two years has been downgrading posts based on the amount of time Facebook users spend on the article after they click the headline.

In a post today, Facebook said that its current plan of attack involved cataloging “tens of thousands” of headlines, which were then analyzed by a team of employees that decided if the headlines withheld pertinent information or were misleading about the accompanying article. The team apparently double-checked its work, and “from there, we built a system that looks at the set of clickbait headlines to determine what phrases are commonly used in clickbait headlines that are not used in other headlines,” Facebook wrote in a press release today. “This is similar to how many e-mail spam filters work.”

Facebook added that its new system, instructed by the categorizations of human employees, would continue to actively learn which sites and Facebook Pages produce clickbait.

Headlines that qualify as clickbait appear lower in a person’s newsfeed. As websites stop using clickbait headlines, Facebook's learning system will be less likely to relegate their articles to the bottom of the newsfeed.

The social media site said that reducing clickbait headlines would facilitate "authentic" communication between its users. Facebook added that most regular users would not see a change, but "websites and Pages who rely on clickbait-style headlines should expect their distribution to decrease."

"Pages should avoid headlines that withhold information required to understand what the content of the article is and headlines that exaggerate the article to create misleading expectations," the company wrote today.

Channel Ars Technica