Positions, Factions and Mandates: Applying Quantitative Text Analysis to Self-Reported Biographical Notes from the Members of the 17th German Bundestag

Abstract

Techniques of quantitative text analysis have successfully been utilized to extract policy positions from party manifestos and parliamentary speeches. This paper discusses the application of quantitative text analysis to new types of texts using the example of self-reported biographical notes from the Members of the German Parliament (MP). Arguing that party- and mandate-specific recruitment patterns shape the vocabulary MPs’ utilize in their biographical notes, we scale these texts using the word-fish/Austin approach. For the first time, we get a measure of the positions of all MP in the German Bundestag. In the course of the empirical study we show that this texts balance between the reporting of political careers on the one hand and strategic political communication on the other. We conclude that quantitative text analysis puts rather high requirements on the structure of the text corpus. The more successful external and formative factors, such as the purpose, context and length of the documents, are kept constant, the more helpful is quantitative text analysis for the identification of a substantially meaningful dimension.