Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
6-2020
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.
Discipline
Numerical Analysis and Scientific Computing
Research Areas
Data Science and Engineering
Publication
Proceedings of the International AAAI Conference on Web and Social Media
First Page
939
Last Page
943
ISBN
9781577358237
Publisher
AAAI
City or Country
California, USA
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.