mlsanityData to 14 Oct 2026

Between welcome culture and border fence. A dataset on the European refugee crisis in German newspaper reports

arXiv 2111.10142 ↗First posted 19 Nov 2021cs.CLcited by 1

Not on the map. Why?

Abstract (arXiv)

Newspaper reports provide a rich source of information on the unfolding of public debate on specific policy fields that can serve as basis for inquiry in political science. Such debates are often triggered by critical events, which attract public attention and incite the reactions of political actors: crisis sparks the debate. However, due to the challenges of reliable annotation and modeling, few large-scale datasets with high-quality annotation are available. This paper introduces DebateNet2.0, which traces the political discourse on the European refugee crisis in the German quality newspaper taz during the year 2015. The core units of our annotation are political claims (requests for specific actions to be taken within the policy field) and the actors who make them (politicians, parties, etc.). The contribution of this paper is twofold. First, we document and release DebateNet2.0 along with its companion R package, mardyR, guiding the reader through the practical and conceptual issues related to the annotation of policy debates in newspapers. Second, we outline and apply a Discourse Network Analysis (DNA) to DebateNet2.0, comparing two crucial moments of the policy debate on the 'refugee crisis': the migration flux through the Mediterranean in April/May and the one along the Balkan route in September/October. Besides the released resources and the case-study, our contribution is also methodological: we talk the reader through the steps from a newspaper article to a discourse network, demonstrating that there is not just one discourse network for the German migration debate, but multiple ones, depending on the topic of interest (political actors, policy fields, time spans).

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 3 of its 40 references that are in the map. First posted on arXiv 19 Nov 2021.

Builds on

3 of 40 references.

References · 3

  1. 2016Bag of Tricks for Efficient Text Classificationcited by 876
  2. 2016Parsing Argumentation Structures in Persuasive Essayscited by 101
  3. 2018Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need!cited by 16

Built on by

Cited by year

Citing papers per year: 2024: 1.

1 paper.