How Facebook users can protect against fake news
Facebook has just two goals in assembling each user’s News Feed:
- Show the smallest number of ads that produce the highest clickthrough yield for an individual user.
- Increase the amount of time an individual user spends interacting with his or her News Feed so the span of posts can be enlarged and the number of ad impressions increased.
It is that simple. But how those are done is not simple.
Facebook uses artificial intelligence (AI), machine learning (ML) specifically, to choose what a user sees in his or her Facebook News Feed. In other words, the News Feed is personalized for each user.
Short explanation of how machine learning works
An over simplified explanation about machine learning will help to understand how to keep fake news and other content the user doesn’t want to see out of his or her News Feed. There are two stages to ML: building and training the model and inference or running the model. There are off-the-shelf and open-source ML packages, such as Tensorflow, Torch and the Cognitive Toolkit. These ML tools are used to build a prediction model and train it to predict something with a high probability of accuracy that the prediction is accurate.
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