Get Russian Poetry Data

To get a zip archive of Russian poetry, visit:

https://s3-us-west-2.amazonaws.com/lab-workshops/russian-poetry.zip

Then move this directory to your Desktop to make it easier to find.

Default Install

1. Install the Anaconda Python 2.7 Distribution - click on "Graphical Installer" under Python 2.7

2. Open a Terminal (Mac and Linux) or PowerShell (Windows).

3. Run pip install --pre topicexplorer -i https://inpho.cogs.indiana.edu/pypi/.

   Note: --pre has two - characters. When the 1.0 release happens, --pre will no longer be necessary.

4. Test installation by typing topicexplorer -h to print usage instructions.

Generating Topics

1. Initialize the Topic Explorer on a file, folder of text files, or folder of folders:

   topicexplorer init insertPathToCorpus
   #for example: topicexplorer init Desktop/wikimedia_russian_texts/txt
   

   When prompted, name your corpus (ex: wikimedia_russian_texts).

   The init command will generate a configuration file called CONFIG.

2. Set a min and max frequency for word occurence:

   topicexplorer prep insertPathToCorpus
   #for example: topicexplorer prep Desktop/wikimedia_russian_texts/txt
   

   When prompted, enter max number (ex: 500).

   When prompted, enter min number (ex: 1).

3. Train LDA models using the on-screen instructions:

   topicexplorer train CONFIG
   #for example: topicexplorer train Desktop/wikimedia_russian_texts/txt.ini
   

   When prompted, specify the number of topics you would like (defaults: 20, 40, 60, 80).

   When prompted, specify the number of training iterations (default: 200).

4. Launch the topic explorer:

   topicexplorer launch CONFIG
   #for example: topicexplorer launch Desktop/wikimedia_russian_texts/txt
   

5. Press Ctrl+C to quit all servers.