Computergestützte Textanalysen
Author:
Publisher
Springer Fachmedien Wiesbaden
Link
http://link.springer.com/content/pdf/10.1007/978-3-658-16937-4_38-1
Reference47 articles.
1. Atteveldt, Van, Jan Kleinnijenhuis Wouter, Nel Ruigrok, und Stefan Schlobach. 2008. Good news or bad news? Conducting sentiment analysis on Dutch text to distinguish between positive and negative relations. Journal of Information Technology & Politics 5(1): 73–94.
2. Benoit, Kenneth. 2017. quanteda: Quantitative analysis of textual data. https://doi.org/10.5281/zenodo.1004683 , R package version 0.99.22. http://quanteda.io .
3. Benoit, Kenneth, und Michael Laver. 2008. Compared to What? A Comment on ‚A Robust Transformation Procedure for Interpreting Political Text‘ by Martin und Vanberg. Political Analysis 16(1): 101–111.
4. Bernauer, Julian, und Thomas Bräuninger. 2009. Intra-Party Preference Heterogeneity und Faction Membership in the 15th German Bundestag: A Computational Text Analysis of Parliamentary Speeches. German Politics 18(3): 385–402.
5. Blei, David, Andrew Ng, und Michael Jordan. 2003. Latent dirichlet allocation. Journal of Machine Learning Research 3:993–1022.
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