Open Access Journal

ISSN: 2183-2439

Article | Open Access

Political Scandals in Germany (2001–2023): A Systematic Approach to Building a Public Dataset

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Abstract:  Political scandals are recurrent across democratic systems, yet research often focuses on isolated, high-profile cases, limiting generalizability and comparability. While some studies examine broader collections of scandals to identify generalizable patterns, they rarely make underlying data publicly available—restricting opportunities for replication, validation, and comparative studies. This article addresses these limitations by introducing an open-access dataset of political scandals and scandalization attempts involving federal-level politicians in Germany between 2001 and 2023. The dataset is based on a content analysis of newspaper coverage from four national-level outlets: Die Tageszeitung, Der Spiegel, Die Zeit, and Die Welt. An initial corpus of 31,274 documents was filtered to include those in which the full names of federal politicians co-occurred with the keywords Skandal (scandal) or Affäre (affair). Manual coding identified scandal-related content and assigned it to unique cases. Documents were annotated with metadata (e.g., outlet, publication date) and contextual variables (e.g., party affiliation, government/opposition status, gender). The final dataset contains structured data derived from 3,005 articles linked to 199 scandals and scandalization attempts, with over 10 variables per observation capturing publication metadata and political context. The dataset is accessible via an online repository and a web application for filtering and visualizing scandal cases and associated media coverage. The article discusses use cases for the dataset and describes how the approach can be applied across different political and media systems to produce comparable datasets.

Keywords:  content analysis; dataset; German media; media coverage; open science; political affair; political scandal

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DOI: https://doi.org/10.17645/mac.12032



© Jan Dvorak. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0), which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.

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