AI RESEARCH
A Comparative Evaluation of Structural Topic Models and BERTopic for Short, Open-Ended Survey Responses
arXiv CS.CL
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ArXi:2605.23093v1 Announce Type: new Topic modeling in applied psychology increasingly spans two methodological traditions: probabilistic bag-of-words models and newer embedding-based approaches. Yet many evaluations of these methods rely on longer and cleaner benchmark corpora, leaving less guidance for short, open-ended survey responses. This paper compares Structural Topic Models (STM), a probabilistic topic model, and BERTopic, an embedding-based model, for analyzing open-ended survey responses.