07/06/2020

Empirical Evaluation of Three Common Assumptions in Building Political Media Bias Datasets

Soumen Ganguly, Juhi Kulshrestha, Jisun An, Haewoon Kwak

Keywords: articles, attention, bias, building, common, news, news articles, political, sources

Abstract: In this work, we empirically validate three common assumptions in building political media bias datasets, which are (i) labelers´ political leanings do not affect labeling tasks; (ii) news articles follow their source outlet´s political leaning; and (iii) political leaning of a news outlet is stable across different topics. We build a ground-truth dataset of manually annotated article-level political leaning and validate the three assumptions. Our findings warn that the three assumptions could be invalid even for a small dataset. We hope that our work calls attention to the (in)validity of common assumptions in building political media bias datasets.

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