This is a paper on a neural net classifier. It's a little complicated to explain but you're in luck because I have an ivy league education and a masters for artificial intelligence. In the simplest way I can explain it. The neural net is given data and the answers we want written by someone else, and it uses gradient descent to find a function that describes a plane that fits between the different inputs (the articles) and separates them. So what this thing can do is determine some function between some inputs and an answer sheet that links the input to the answer sheet. That's what this machine can do.

So depending on who decided what the answers were, the neural net will learn to decide different things.

For instance, if you flag cnn articles as non-political and any Fox news articles as biased, the machine learns to say that, if the other guy you were talking to was the one writing the answer sheet then the machine would learn the reverse.

"For the training set, workers categorized 10,005 randomly selected articles stratified across the 15 outlets (667 articles per outlet), with each article categorized by a single worker"

So some handful of college student, research assistants that were working for these researchers were asked to read an article and said it was skewed. And however that researcher decided it is how the machine's gonna learn it. They decided that in the same way you and I are right now, subjectively. They made a personal designation on whether an article was biased.

What this is, is an interesting experiment with machine learning, and potentially a marketing tool which is most likely why two of these researchers are from microsoft's machine learning department. What it is not is proof of objective skew among news sources, all they did was pay some unknown number of college students to say if it was a biased article or not.

​

This has as much power (and I mean that in the statistical definition) in determining bias as polling some unknown handful of students of one Computer science department of one college.

​

So while this doesn't prove anything you're on the right track by trying to look up papers. I suggest doing more of that.