Social scientists are now in an era of data abundance, and machine learning tools are
increasingly used to extract meaning from data sets both massive and small. We explain …

We propose and explore the possibility that language models can be studied as effective
proxies for specific human subpopulations in social science research. Practical and …

This study examines the performance of open-source Large Language Models (LLMs) in
text annotation tasks and compares it with proprietary models like Chat-GPT and human …

Supervised machine learning is an increasingly popular tool for analyzing large political text
corpora. The main disadvantage of supervised machine learning is the need for thousands …

What is the role of social media in political agenda setting? Digital platforms have reduced
the gatekeeping power of traditional media and, potentially, they have increased the …

A guide for using computational text analysis to learn about the social world From social
media posts and text messages to digital government documents and archives, researchers …

Hyperparameters critically influence how well machine learning models perform on unseen,
out-of-sample data. Systematically comparing the performance of different hyperparameter …

This study analyzes large language models (LLMs) as a methodology for computational
sociology, focusing on applications to supervised text classification. We consider how the …

This paper studies the performance of open-source Large Language Models (LLMs) in text
classification tasks typical for political science research. By examining tasks like stance …

The framing of political issues can influence policy and public opinion. Even though the
public plays a key role in creating and spreading frames, little is known about how ordinary …