Machine-Learning media bias

Kavli Affiliate: Max Tegmark

| First 5 Authors: Samantha D’Alonzo, Max Tegmark, , ,

| Summary:

We present an automated method for measuring media bias. Inferring which
newspaper published a given article, based only on the frequencies with which
it uses different phrases, leads to a conditional probability distribution
whose analysis lets us automatically map newspapers and phrases into a bias
space. By analyzing roughly a million articles from roughly a hundred
newspapers for bias in dozens of news topics, our method maps newspapers into a
two-dimensional bias landscape that agrees well with previous bias
classifications based on human judgement. One dimension can be interpreted as
traditional left-right bias, the other as establishment bias. This means that
although news bias is inherently political, its measurement need not be.

| Search Query: ArXiv Query: search_query=au:”Max Tegmark”&id_list=&start=0&max_results=10

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