text-analysis

Session on text analysis with NLTK, including discussion of cleaning data, creating text corpora, and analyzing texts programmatically.

View the Project on GitHub dhsouthbend/text-analysis

Introduction to Text Analysis with Python and the Natural Language ToolKit (NLTK)

Digital technologies have made vast amounts of text available to researchers, and this same technological moment has provided us with the capacity to analyze that text. The first step in that analysis is to transform texts designed for human consumption into a form a computer can analyze.

Using Python and the Natural Language ToolKit (commonly called NLTK), this workshop introduces strategies to turn qualitative texts into quantitative objects. Through that process, we will present a variety of strategies for simple analysis of text-based data.

By the end of this workshop, you will be able to:

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Overview
Text as Data
Cleaning and Normalizing
NLTK Methods with the NLTK Corpus
Searching For Words
Positioning Words
Built-In Python Functions
Making Your Own Corpus: Data Cleaning
Make Your Own Corpus
Part-of-Speech Tagging
Conclusion


Session Leader: Caroline McCraw Based on previous work by: Michelle A. McSweeney, PhD and Rachel Rakov

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