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Software Requirements

R and RStudio

R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.

####Windows

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE.

####Mac OS X

Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.

####Linux

You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo yum install R). Also, please install the RStudio IDE.

Java

Make sure that your Java Runtime-Environment (JRE) installation is up to date. Your JRE version should be at least 1.7.

####Windows

For Windows, visit this page to download Windows x64 package of JRE JRE version 8, and then follow the installation instructions. You can browse to this website to test your installation. (Note: This won't work in Chrome)

####Mac OS X

If your OS is up-to-date, you should have at least Java 1.7. You can update your OS using Software Update.

See here for more detailed information.

You can browse to this website to test your installation. (Note: This won't work in Chrome)

####Linux

For Linux, visit this page to download Linux x64 package of JRE JRE version 8, and then follow the installation instructions.

Required R Packages

  1. tm # text mining in R
  2. RTextTools # a machine learning package for text classification
  3. qdap # quantiative discourse analysis
  4. qdapDictionaries # for sentiment analysis, etc
  5. entropy # tools applying Information Theory
  6. dplyr # data preparation and pipes $>$
  7. ggplot2 # for plotting
  8. SnowballC # for stemming
  9. matrixStats # for stats
  10. data.table # for easier data manipulation
  11. scales # to help us plot
  12. lsa # latent semantic analysis
  13. cluster # for clustering analysis
  14. fpc # flexible procedures for clustering
  15. mallet # a wrapper around the Java machine learning tool MALLET
  16. wordcloud # to visualize wordclouds
  17. rJava # dependency for mallet
  18. Any dependencies to the packages above.

Installation

To install these packages, you can open RStudio and use the command install.packages() in the console. For example, to install the tm package, you would type:

install.packages('tm')

Make sure to use quotation marks around the name of the package.

If RStudio returns an error message, go to "Preferences" and check the "Packages" section. Under "CRAN Mirror," if no mirror is selected, choose "Global (CDN) - RStudio". Otherwise, check your internet connection.