How to use LLMs for Text Analysis
Petter Törnberg
This guide introduces Large Language Models (LLM) as a highly versatile text
analysis method within the social sciences. As LLMs are easy-to-use, cheap,
fast, and applicable on a broad range of text analysis tasks, ranging from text
annotation and classification to sentiment analysis and critical discourse
analysis, many scholars believe that LLMs will transform how we do text
analysis. This how-to guide is aimed at students and researchers with limited
programming experience, and offers a simple introduction to how LLMs can be
used for text analysis in your own research project, as well as advice on best
practices. We will go through each of the steps of analyzing textual data with
LLMs using Python: installing the software, setting up the API, loading the
data, developing an analysis prompt, analyzing the text, and validating the
results. As an illustrative example, we will use the challenging task of
identifying populism in political texts, and show how LLMs move beyond the
existing state-of-the-art.