Machine-Learning media bias

Samantha D'Alonzo; Max Tegmark

doi:10.1371/journal.pone.0271947

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arXiv · 2109.00024

Machine-Learning media bias

Samantha D'Alonzo·Max Tegmark

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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.

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Samantha D'Alonzo, Max Tegmark. 2021-08-31. Machine-Learning media bias. https://doi.org/10.1371/journal.pone.0271947

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