Comparing with Python: Text Analysis in Stata

TL;DR

This paper demonstrates how to perform text analysis using Stata, comparing its methods and efficiency with Python, to expand the toolkit for researchers working with unstructured textual data.

Contribution

It provides a practical, step-by-step guide for conducting text analysis in Stata and compares its performance with Python, which is rarely documented.

Findings

Stata can effectively perform basic text analysis tasks.

Python generally runs faster than Stata for text processing.

The paper offers practical examples and code for Stata-based text analysis.

Abstract

Text analysis is the process of constructing structured data from unstructured textual content, usually implemented in Python. In terms of the principles of text analysis, a computer program with the ability to read a file and match it with a regular expression is all that is needed for basic text analysis. However, few researchers have used Stata as their main text analysis tool. In this paper, I will take a step-by-step approach to the practical process, giving examples of how text analysis can be performed with Stata, and comparing the code and running time with Python.