Towards Coding Social Science Datasets with Language Models

Understand

Researchers often rely on humans to code (label, annotate, etc.) large sets of texts.

• This kind of human coding forms an important part of social science research, yet the coding process is both resource intensive and highly variable from application to application.
• In some cases, efforts to automate this process have achieved human-level accuracies, but to achieve this, these attempts frequently rely on thousands of hand-labeled training examples, which makes them inapplicable to small-scale research studies and costly for large ones.
• Recent advances in a specific kind of artificial intelligence tool - language models (LMs) - provide a solution to this problem.