Machine-learning media bias

Samantha D’Alonzo and Max Tegmark

PLOS ONE, 2022, vol. 17, issue 8, 1-24

Abstract: 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.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0271947

DOI: 10.1371/journal.pone.0271947

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