Textual Measures of Populism (TEMPOP) for the Analysis of Party Competition and Political Behaviour

Research question/goal: 

The project "Textual Measures of Populism (TEMPOP) for the Analysis of Party Competition and Political Behaviour" seeks to contribute scientifically to research on populism, party competition, and political behaviour in conceptual, methodological, and analytical terms. A quantification of populism eases the scientific study as well as the societal discussion of populism and its causes or consequences. In the course of the project, the information obtained on the degree of populism of politicians and political parties is used to answer research questions on patterns of political competition between populist and mainstream parties as well as on the impact on individual political behaviour. The project applies statistical models measuring populism from political text (party manifestos, political speeches and (social) media), thereby crossing contextual and language barriers, and contributes to the analysis of causes and consequences of populism.

Current stage: 

Machine learning and natural language processing tools are currently being tested to identify practical methods for measuring populism using texts. In doing so, we focus on the annotation of text to obtain informed machine learning algorithms for classification and scaling, and the construction of a TEMPOP database with a web application interface in the form of a "Shiny-App". The aim remains submitting a grant proposal to the DFG.

Fact sheet

2018 to 2023
in preparation
Data Sources: 
party manifestos, political speeches, Tweets
Geographic Space: 
16 established European democracies