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BERTopic outperforms STM in analyzing short survey responses

A new paper compares two topic modeling approaches, Structural Topic Models (STM) and BERTopic, for analyzing short, open-ended survey responses. The study found that BERTopic generally produced more coherent and interpretable topics, especially when using a novel contextual augmentation strategy. While STM offers stronger inferential capabilities for covariate analysis, BERTopic provides more descriptive comparisons, suggesting both methods have complementary strengths for social science research. AI

IMPACT Provides guidance on selecting and combining topic modeling approaches for analyzing short, open-ended survey data.

RANK_REASON The cluster contains an academic paper comparing two topic modeling techniques.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Yan Jiang, Sihong Liu, Philip A. Fisher ·

    A Comparative Evaluation of Structural Topic Models and BERTopic for Short, Open-Ended Survey Responses

    arXiv:2605.23093v1 Announce Type: new Abstract: 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 benchmar…

  2. arXiv cs.CL TIER_1 English(EN) · Philip A. Fisher ·

    A Comparative Evaluation of Structural Topic Models and BERTopic for Short, Open-Ended Survey Responses

    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…