Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/180156 
Autor:innen: 
Erscheinungsjahr: 
2017
Schriftenreihe/Nr.: 
BGPE Discussion Paper No. 177
Verlag: 
Friedrich-Alexander-Universität Erlangen-Nürnberg, Bavarian Graduate Program in Economics (BGPE), Nürnberg
Zusammenfassung: 
Digitization and computer science have established a whole new set of methods to analyze large collections of texts. One of these methods is particularly promising for economic historians: topic models, statistical algorithms that automatically infer themes from large collections of texts. In this article, I present an introduction to topic modeling and give a very first review on the research using topic models. I illustrate their capacity by applying them on 2.675 articles published in the Journal of Economic History between 1941 and 2016. This contributes to traditional research on the JEH and to current research on the cliometric revolution.
Schlagwörter: 
Economic History
Topic Models
Latent Dirichlet Allocation
Cliometrics
Digitization
Methodology
JEL: 
A12
C18
N01
Dokumentart: 
Working Paper

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