Using LLM-generated text augmentations as input to BERTopic yields interpretable, actor-specific topics for targeted social science questions in short-text corpora.
A bayesian hierarchical topic model for political texts: Measuring expressed agendas in senate press releases
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation
Using LLM-generated text augmentations as input to BERTopic yields interpretable, actor-specific topics for targeted social science questions in short-text corpora.