June 2017
Intermediate to advanced
191 pages
4h 29m
English
Content preview from Text Mining with R
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Bibliography
Abelson, Hal. 2008. “Foreword.” In Essentials of Programming Languages, 3rd Edition. The MIT Press.
Arnold, Taylor B. 2016. “cleanNLP: A Tidy Data Model for Natural Language Processing.” https://cran.r-project.org/package=cleanNLP.
Arnold, Taylor, and Lauren Tilton. 2016. “coreNLP: Wrappers Around Stanford Corenlp Tools.” https://cran.r-project.org/package=coreNLP.
Benoit, Kenneth, and Paul Nulty. 2016. “quanteda: Quantitative Analysis of Textual Data.” https://CRAN.R-project.org/package=quanteda.
Feinerer, Ingo, Kurt Hornik, and David Meyer. 2008. “Text Mining Infrastructure in R.” Journal of Statistical Software 25 (5): 1–54. http://www.jstatsoft.org/v25/i05/.
Loughran, Tim, and Bill McDonald. 2011. “When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10-Ks.” The Journal of Finance 66 (1): 35–65. doi: https://doi.org/10.1111/j.1540-6261.2010.01625.x.
Mimno, David. 2013. “mallet: A Wrapper Around the Java Machine Learning Tool Mallet.” https://cran.r-project.org/package=mallet.
Mullen, Lincoln. 2016. “tokenizers: A Consistent Interface to Tokenize Natural Language Text.” https://cran.r-project.org/package=tokenizers.
Pedersen, Thomas Lin. 2017. “ggraph: An Implementation of Grammar of Graphics for Graphs and Networks.” https://cran.r-project.org/package=ggraph.
Rinker, Tyler W. 2017. “sentimentr: Calculate Text Polarity Sentiment.” Buffalo, New York: University at Buffalo/SUNY. http://github.com/trinker/sentimentr.
Robinson, David. 2016. “gutenbergr: ...
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