Analyzing political speeches presents a challenge: topic models identify themes but labeling them requires human effort. This study introduces transfer topic labeling, which uses domain-specific dictionaries to automate the process.

We tested this method on all UK House of Commons debates from 1935-2014—using CAP coding instructions—to show its potential for political science research. Our evaluation against expert coding revealed promising results:

• Method: Transfer topic modeling using domain-specific codebooks as a knowledge base.

• Performance: Simple to implement and compared well with human experts.

• Advantage: Outperformed neural network models in most cases.

This approach offers an accessible, replicable solution for automatically labeling themes.