Everyday numerous photos and videos are posted on Facebook. All of them are not appropriate so it becomes necessary to check their facts. It would help to determine their accuracy. Facebook has declared that it is going to increase its fact-checking endeavors in order to check the accurateness of videos and photos. Until now Facebook’s efforts are focused for reviewing articles in order to prevent spreading fake news. Now all the 27 partners of Facebook for fact-checking across 17 countries will give emphasis to decrease spreading of wrong information through videos and photos. This will help users getting filtered and appropriate information through text, video and photos.

Role of Fact-Checking feature of Facebook

A blend of Facebook users’ feedback and machine learning is used by fact-checking procedure of Facebook to detect false content potentially. Once false content are detected, it is then sent to third party for fact-checking and performing review by them. It is also possible by fact-checkers to give content individually. It helps them giving their own feedback about the fact. It helps Facebook realizing their views about the content therefore they can handle it accordingly. This way false content, videos and photos on Facebook can be prevented to be spread across the users.

Facebook has given explanation how this system is applicable to videos and photos specifically. All the third-party partners of Facebook have expertise to assess videos and photos. They have exclusive training in visual verification systems. It includes analyzing image metadata, searching reverse image and information like where and when the video or photo was taken. These skills are added with other journalistic procedure like academics or government agencies, using research from experts by fact-checkers. They can judge the falsity or truth of a video or photo by the combined skills and knowledge.

OCR (optical character recognition) feature is started by Facebook for removing text from photos and compare them with headlines from the articles of fact-checkers. New methods are used by company to identify if a manipulation took place in video or photo. When misleading or false content is detected, one of the following ratings is given:

Out of context

Fabricated or manipulated

Audio or text claim

Machine learning model of Facebook is improved further by using the ratings of fact-checkers about videos and photos.

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