DpgMedia2019: A Dutch News Dataset for Partisanship Detection
Chia-Lun Yeh, Babak Loni, Mari\"elle Hendriks, Henrike Reinhardt, Anne, Schuth
TL;DR
This paper introduces a large Dutch news dataset with publisher and article-level partisanship labels, enabling research on media bias and partisanship detection in Dutch news articles.
Contribution
The paper provides a new Dutch news dataset with over 100K publisher-labeled articles and 776 crowd-labeled articles, detailing its collection, annotation, and potential applications.
Findings
Dataset contains over 100K publisher-labeled articles
Crowdsourced 776 articles with detailed labels
Facilitates research on media partisanship in Dutch news
Abstract
We present a new Dutch news dataset with labeled partisanship. The dataset contains more than 100K articles that are labeled on the publisher level and 776 articles that were crowdsourced using an internal survey platform and labeled on the article level. In this paper, we document our original motivation, the collection and annotation process, limitations, and applications.
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Taxonomy
TopicsTopic Modeling · Misinformation and Its Impacts · Hate Speech and Cyberbullying Detection