Like-baiting & Click-baiting - What it's all about and why Facebook wants to stamp it out.

You’ve probably heard that Facebook has been making changes to its algorithm recently, both back in April to combat ‘like-baiting’ and more recently in August to stamp out ‘click-baiting’ too. So what is it all about?

What do the terms mean?

Facebook’s newsroom describes like-baiting as: "when a post explicitly asks News Feed readers to like, comment or share the post in order to get additional distribution beyond what the post would normally receive."

The Facebook algorithm will send posts to the top of your News Feed if more people have Liked, Shared or Commented on the posts. Therefore, when users respond to posts in any of these ways, the posts will get much more widely circulated.

However, now Facebook wants to cut back on posts like this that don’t actually provide any content of value to the user when they click on them. They are often described as ‘request for like’ posts.

Click-baiting, on the other hand, is when posts use, according to Facebook: "inaccurate language or formatting to try and trick people into clicking through to a website that contains only ads or a combination of frequently circulated content and ads."

Such posts might use teaser photos or a misleading quote or headline to take people to a page that wasn’t what they were expecting.

Facebook undertook a survey amongst some of its users, and the results showed that the users found ‘like-bait’ type posts to be 15% less relevant than other posts on their News Feeds. Overall they gave a less enjoyable experience.

How can Facebook tell if the post is like or click bait?

Facebook has stated that it now aims to prevent these posts getting widely circulated and can detect when they are being used. In the case of click baits, It can assess how long users spend reading a post that they have clicked on. The longer time spent, the more likely it is that the user has found something of value to them, whilst if they come straight back to Facebook its more likely they have found something of no value or not what they were expecting.

Also taken into consideration is the users reaction to a post. For example, if the post is then commented on or shared, the likelihood again is that valuable content was found after clicking.

How can marketers ensure their posts don’t fall into these categories?

Facebook is keen to promote the use of sharing links in the native link format. When drafting a post and users enter a link, a box appears with perhaps a picture but also some text. It is this text that then allows the reader to decide whether to click on the link or not, as it contains some additional information about the link such as the beginning of an article.

They have also stated that these changes to the algorithm won’t adversely affect other Pages who don’t use these techniques, if anything they should see a slight increase in engagement as less ‘like-baiting’ and ‘click-baiting’ posts appear on News Feeds. It has promised to now “prioritize showing links in the link-format, and show fewer links shared in captions or status updates.”


Lynn Scott

Lynn Scott

Social Media Consultant at The Fountains Agency

My company is The Fountains Agency, and we specialise in social media marketing and training. I offer advice to businesses on social media including setting up accounts, building strategy, managing content marketing, optimisation and ROI. I also offer specialised training for individuals or businesses. Networks include Facebook, Twitter, LinkedIn, Instagram, Pinterest, Google+ and Wordpress for Blogging.


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Ling Lee

Ling Lee , at Digital Marketing and Personal Branding

Thanks for the great article Lynn! It's awesome how finally Facebook is catching up with the times and make it harder for social media marketers to try to cheat the system. I think Youtube is doing a similar thing.

Lisa Ormenyessy

Lisa Ormenyessy , Business Coach and Marketing Specialist at Straight Talk Group

Thanks Lynn. Finally Facebook is doing something. Click bait in particular is a pet hate.