Tutorial 2: Extracting Information from Documents

Tutorial description: This workshop provides an introduction to information extraction for social science–techniques for identifying specific words, phrases, or pieces of information contained within documents. It focuses on two common techniques, named entity recognition and dependency parses, and shows how they can provide useful descriptive data about the civil war in Syria. The workshop uses the Python library spaCy, but no previous experience is needed beyond familiarity with Python.

Tutorial host:  Andrew Halterman

Colab notebook (accompanying code and slides):
https://colab.research.google.com/drive/1U6x-3OVCGtx9CBZvzdJi8mhTxCx8k4Ie?usp=sharing

This is part of a larger tutorial series, NLP+CSS 201: Beyond the basics, which is organized by Ian Stewart and Katherine Keith. Website: https://nlp-css-201-tutorials.github.io/nlp-css-201-tutorials/

Видео Tutorial 2: Extracting Information from Documents канала NLP and CSS 201: Beyond the Basics