Introduction to text analysis in python

Speaker: Austin van Loon (SICSS-Princeton 19; Ph.D. student in Sociology at Stanford University)

Description: The increased availability of machine-readable text provides a unique opportunity for social scientists, granting us unprecedented access to many aspects of both historical and contemporary social life. This tutorial aims to introduce researchers to text analysis in Python, an open-source programming language. Specifically, I’ll seek to cover: using the new Twitter API v2, pre-processing text, visualizing patterns in data, and a few conceptually accessible methods for quantitatively analyzing unigram frequencies (the “dictionary method” and differential language analysis). The tutorial is divided between a publicly available Google Colab notebook (see below) which provides documented, step-by-step example code, and a live session in which I review key points from the notebook and discuss the methods explored therein more analytically.

Materials: https://colab.research.google.com/dri...