Text Mining with Python

Neal Caren and Katherine Furl
University of North Carolina, Chapel Hill

1. Getting started
   1. Installing your tools
   2. Using Jupyter Notebooks
2. Basics
   1. Python 101
   2. Pandas 101
3. Collecting Texts
   1. Web APIs
   2. Web Scraping
   3. Bulk Downloading Web pages
   4. Other files
   5. PDFs
   6. Word Documents - ?
   7. Case Study: Twitter with Twint
   8. Case Study: Reddit
4. Counting words
   1. Frequencies
   2. Sentiment
   3. Case Study: ???
5. Natural Language Processing
   1. Part of speech tagging
   2. Named Entity Extraction
   3. Word vectors
   4. Case Study: ???
6. Analysis
   1. Classification
   2. Topic Modeling
   3. Case Study: ???
7. Appendix
   1. Pipelines - ?
   2. Train/test out of sample
   3. Bigrams?
   4. Teaching with Notebooks