Helpful resources for learning R
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1_r_calculator.Rmd
1_r_calculator.html
1_r_calculator.md
1_r_calculator.pdf
2_playing.Rmd
2_playing.html
2_playing.md
2_playing.pdf
3_organizing.Rmd
3_organizing.html
3_organizing.md
3_organizing.pdf
4_transforming.Rmd
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4_transforming.md
4_transforming.pdf
5_modeling.Rmd
5_modeling.html
5_modeling.md
5_modeling.pdf
6_visualization.Rmd
6_visualization.html
6_visualization.md
7_timeseries.Rmd
7_timeseries.html
7_timeseries.md
8_multilevel.Rmd
8_multilevel.html
8_multilevel.md
9_programming.Rmd
9_programming.html
LICENSE
README.md
amcat.Rmd
amcat.pdf
amcatr.Rmd
amcatr.pdf
clauses.Rmd
clauses.html
clauses.md
comparing.Rmd
comparing.pdf
corpus.Rmd
corpus.html
corpus.md
corpus.pdf
ex_tweets.rds
functions.md
install_required_packages.r
lda.Rmd
lda.html
lda.md
lda.pdf
learningr.Rproj
ml.Rmd
ml.pdf
rvest.Rpres
rvest.html
semnet.Rmd
semnet.html
semnet.pdf
sentiment.Rmd
sentiment.pdf
sentiment_data.Rmd
sentiment_data.pdf
text_1_corpus.Rmd
text_1_corpus.html
text_1_corpus.md
text_2_lda.Rmd
text_2_lda.html
text_2_lda.md
text_3_lemma.Rmd
text_3_lemma.html
text_3_lemma.md
text_4_texttools.Rmd
text_4_texttools.html
text_4_texttools.md
twitter.Rmd
twitter.html
twitter_facebook.Rmd
twitter_facebook.pdf
twitter_sna.Rmd
twitter_sna.pdf
visualization.Rmd
visualization.pdf

README.md

Learning R

R is a very powerful and flexible statistics package and programming language.

This repository contains a number of 'howto' files aimed to providing an introduction to R and some os its possibilities.

You can install R and RStudio with the following links:

Some other great sites for learning R are:

General Howto's

(see also this short overview of useful R functions)

Dealing with textual data

For textual data, we have also developed two R packages to communicate with the AmCAT text analysis framework and to deal with corpus analysis and topic models. We also wrote two relevant howto's:

Below are also some handouts that do not depend on AmCAT, based on a Dutch data set:

Network Analysis

(The last part of the 'semantic network analysis' demo above also has a simplistic network analysis at the end)