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From STM to GPT: A Comparative Study of Topic Modeling Methods for AI in Dentistry

Year: 2025

Type: article

Abstract: This study presents a comprehensive topic modeling analysis of scientific abstracts in the field of artificial intelligence (AI) applied to dentistry. Three complementary approaches were compared: Structural Topic Modeling (STM); embedding-based clustering using the Leiden algorithm on OpenAI text embeddings; and zero-shot GPT-based topic modeling

Source: RESEARCH RESULT Theoretical and Applied Linguistics

DOI: 10.18413/2313-8912-2025-11-3-0-5

Authors: Yury A. Ippolitov, Pavel V. Seredin, Tatiana A. Litvinova

Language: English

Topic: Computational and Text Analysis Methods

Subfield: General Social Sciences

Field: Social Sciences

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W4415267884

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