Overview

In this project, we aim to construct a profound dictionary which can be used for automated text analysis. Therefore, we will edit a unique data collection that was initially gathered by qualitative content analysis in the research project “COVFED”. In COVFED, we investigated German federalism in times of the Covid-19 crisis. To this end, we analyzed 212 parliamentary debates on Covid-19, coded 4.610 statements made by the deputies in the German Bundestag and in the 16 state parliaments, and integrated them into a dataset that was subject to various quality checks. The dataset is publicly available at the data repository of GESIS. Due to the exceptional scope and careful qualitative coding, the existing data can be edited to construct a dictionary for automated text analysis(text-as-data). Beyond Covid-19, the dictionary enables a multifaceted data reuse for novel and relevant research projects in the areas of federalism and multi-level politics. The dictionary will also be an innovative contribution to the comparative federalism literature, serving scholars who work on other federal systems as promising starting point for research projects. In the data reuse project, the team at Freie Universität Berlin cooperates with GESIS, the largest European infrastructure institute for the social sciences.

Datasets

• Beltermann, Eric, Antonios Souris, Christoph Nguyen & Sabine Kropp (2024). StateParl. Text Corpus of Speeches in German state parliaments Datenfile Version 1.0.0. GESIS SowiDataNet|datorium. Open Access - available here.

Presentations

• Souris, Antonios: "How do political parties play the federal “blame game”? Exploring discursive strategies in German legislative debates". Presented at DVPW Arbeitskreis Parteienforschung, 10 and 11 October 2024, TU Chemnitz.
• Souris, Antonios, Sabine Kropp: "Blame attribution strategies in cooperative federalism: a dictionary approach." Presented at 2nd IGCOORD Conference, 13 and 14 June 2024, TU Darmstadt.