Textual Analysis using Python for HSS – TextBlob

COURSE DESCRIPTION

This is the third part of a four-part series for humanities and social sciences researchers (HSS) and librarians. 

Textual Analysis using TextBlob focuses enables participants to apply basic coding concepts to text-based analysis. We will use a Python library to import, analyze, explore, and manipulate textual datasets and learn about common natural language processing (NLP) techniques like n-grams and NLP tasks such as word tokenization, parsing, frequency detection, spelling correction, sentiment analysis, classification, and more to explore meaningful trends in language patterns.

It is highly recommended that you complete the 2-part Python series, Introduction to Python & Coding for HSS – Part I & II in the HSS Python Series, before registering for this session. 

You do not need any previous knowledge of the tools that will be presented.

You need a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc) on which you have administrative privileges, as you may need to pre-load specific software packages.