The following text is excerpted from the original text officially released by Facebook. From the official strategy, we can know where they will start, and what analysis and judgment they will make, to find the corresponding solutions and avoidance solutions. At the same time, we can also predict where the review will be triggered or lead to a dead number, to optimize the advertising plan and advertising strategy.
these signals are to help determine whether a post might be clickbait, false news, or other types of inauthentic content.
in the US, the signals for false news include things like whether the post is being shared by a Page that’s spread a lot of false news before,
whether the comments on the post include phrases that indicate readers don’t believe the content is true,
whether someone in the community has marked the post as false news.
Facebook uses a machine learning classifier to compile all of those misinformation signals and — by comparing a given post to past examples of false news
we consider if a post about health exaggerates or misleads — for example, making a sensational claim about a miracle cure.
we consider if a post promotes a product or service based on a health-related claim — for example, promoting a medication or pill claiming to help you lose weight.
Here are six examples Facebook cited as using watchbait:
His Reaction Was Priceless!! 😂😂
THIS IS THE WORST WAY TO WAKE UP!! 😂
And then his GF did this!!!
Absolutely mind-blowing details in the latest recipe from Kai!
Your bestie just sent a crazy message to your girlfriend! 😰😰😰
SHOCKING weather phenomenon could explode your plans!!!