ParlLawSpeech
See parllawspeech.org for image sourcesThe ParlLawSpeech dataset offers 4.02 GB of data in total, including machine-readable full texts of 43,582 bills, 28,124 laws, and 3,092,431 plenary speeches from eight European parliaments covering more than two decades each.
ParlLawSpeech is meant to push the systematic analysis of European democracies with advanced text-as-data/NLP methods. Compared to the other excellent extant political science text corpora (cf. Sebők et al. 2025), it adds two key innovations. First, the bill and law corpora are are among the most encompassing full-text vectors of legal documents handled by parliaments. Second, we provide novel data linkage possibilities by offering a common identifier across bills, corresponding plenary speeches, and finally adopted laws- opening up new analytical opportunities to study the legislative process (basic ideas in the tutorial section).
This dataset is the result of the OPTED Work Package 5 (WP5) led by Sven-Oliver Proksch, Christian Rauh, and Miklós Sebők and funded by the European Union’s Horizon 2020 program (Grant agreement 951832). Our task was to develop different prototypes for improving access to linked parliamentary text data produced in European democracies.
More detailed information is provided on the ParlLawSpeech homepage and the data repository that is permanently stored at GESIS.
I am a Research Associate at the Jacques Delors Centre at the Hertie School and part of the DFG-funded Research Unit “Reconfiguring Europe: Between Competence and Control”, where I work on the Coordination Project. I am also completing my PhD in Political Science at the University of Cologne.
My research focuses on European politics, political communication, public opinion, and crisis governance. I am particularly interested in how citizens, political actors, and institutions respond to political crises and broader political challenges, and how these responses shape European integration, political representation, and institutional change.
Methodologically, I work at the intersection of political science and computational social science. I use large-scale text data, computational text analysis, advanced survey designs, and (quasi-)experiments to study political discourse, public opinion, and political behaviour. I am also interested in building, linking, and analysing large-scale political datasets, particularly institutional text data from parliaments and EU institutions.
Before joining the Hertie School, I worked as a doctoral researcher at the University of Cologne and at GESIS – Leibniz Institute for the Social Sciences, where I worked on election research and data-based knowledge transfer. I also held research assistant positions at the University of Amsterdam, Ghent University, and Humboldt University of Berlin. I hold an M.Sc. in Social Sciences Research from the University of Amsterdam and a B.Sc. in Social Sciences from Humboldt University of Berlin.
I also teach courses on quantitative methods, EU politics, and crisis politics.
Please feel free to explore my work and get in touch.