WIM | Text Mining in Python for Social Scientists

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Date
2020-10-23 (Creation date: 2020-10-23)
Main contributor
Helge-Johannes Marahrens
Summary
Textual data are central to the social sciences. However, they often require several pre-processing steps before they can be utilized for statistical analyses. This workshop introduces a range of Python tools to clean, organize, and analyze textual data. It is intended for researchers who are new to working with textual data, but are familiar with Python or have completed the Introduction to Python workshop. Python is best learned hands-on. Python packages: nltk, fuzzywuzzy, re, glob, sklearn, pandas, numpy, matplotlib
Publisher
IU Workshop in Methods
Collection
Workshop in Methods
Unit
Social Science Research Commons
Related Item
Accompanying materials on IU ScholarWorks 

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