ARTICLE: Quantitative analysis of journalistic texts

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New article by Carina Jacobi, Wouter van Atteveldt and Kasper Welbers introduces a relatively recent tool for quantitative analysis, Latent Dirichlet Analysis. LDA is an unsupervised topic modelling technique that automatically creates “topics”, that is, clusters of words, from a collection of documents. In this article the scholars demonstrate its usefulness for journalism research.

The study shows that LDA is a useful tool for analysing news content in large digital news archives relatively quickly.

Read the free abstract here.

Picture: Video tape archive by DRs Kulturarvsprojekt, licence: CC BY-SA 2.0

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