Hot politics Lab: Topics



Politicians communicate their policy positions, but also stories about their personal lives and their perspective on the world. In doing so, what will they say and how they will say it? How much emotion will they put in their words? How complicated will they make their sentences? By doing this politicians reveal something of their personality. In the Hot Politics Lab, we analyze all preceding questions, and aim to develop a model

that predicts what politicians will say (topic, position) and how they will say this. Are politicians strategic and will they tailor their messages to public opinion, or are politicians unable to adapt, and does personality explain their communication? We will find out.

You will find some of our preliminary findings in the publications, working papers and blogs mentioned below.

work in progress

Applications of automated text analysis measuring topics, ideology, sentiment or even personality are booming in fields like political science and political psychology. These developments are to be applauded as they bring about novel insights about politics using new sources of (unstructured) data. However, a divide exists between work in both disciplines using text as data. In this paper we argue in favor of more integration across disciplinary boundaries, structuring our case around four key issues in the research process: (i) sampling text; (ii) authorship as meta data; (iii) pre- processing text; (iv) analyzing text. Along the way we demonstrate that an assessment of speaker characteristics may crucially depend on the text sources under study, and that the use of senti- ment words correlates with estimates of policy positions, with implications for interpretation of the latter. As such, this paper contributes to a critical discussion about the merits of automated text analysis methods in political psychology and political science, with an eye towards advancing the considerable potential of text as data in the study of politics.

There is some evidence that liberal politicians use more complex language than conservative politicians. This evidence, however, is based on a specific set of speeches of US Congress members and UK members of Parliament. This raises the question whether the relationship between ideology and linguistic complexity is a more general phenomenon or specific to this small group of politicians. To address this question, this paper analyzes 381,609 speeches from five parliaments, from twelve European prime ministers, and from party congresses across time and across countries. Our results replicate and generalize these earlier findings: speakers from culturally liberal parties use more complex language than speakers from culturally conservative parties. Economic left-right differences, on the other hand, are not systematically linked to linguistic complexity.


PDF  Pdf version    Appendix  Appendix    Blog  Blog    Replication Materials  Replication Materials




Gijs Schumacher & Nathalie Giger (2017). Do leadership-dominated parties change more? Journal of Elections, Public Opinion and Parties.

PDF  Replication Materials


Christian Elmelund-Præstekær & Gijs Schumacher (2014). Én for alle og alle for én? Mønstre i og effekter af partiintern uenighed blandt folketingskandidaterne ved 2011-valget. Politica, 46, 3.

PDF  Replication Materials


Gijs Schumacher, Catherine de Vries & Barbara Vis (2013). Why do Parties change Position? Party organization and environmental incentives. Journal of Politics, 75, 2.

PDF  Appendix  Blog  Replication Materials

chapters, data & other




Gijs Schumacher, Martijn Schoonvelde, Denise Traber, Tanushree Dahiya, and Erik de Vries (2016). EUSpeech: A New Dataset of EU Elite Speeches. In Proceedings of the International Conference on the Advances in Computational Analysis of Political Text (PolText 2016), Dubrovnik, 75–80.



Gijs Schumacher, Martijn Schoonvelde, Tanushree Dahiya, and Erik de Vries. (2016). EUSpeech. A Dataset of EU Elite Speeches 2007-2015. Version 2.0.

Replication Materials