Miről írnak a budapesti fine dining éttermek vendégei? Éttermi vendégvélemények témamodellezése neurális témamodellel
DOI:
https://doi.org/10.14267/TURBULL.2025v25n1.2Kulcsszavak:
neurális témamodellezés, éttermi vélemények, fine dining, BERTopicAbsztrakt
A tanulmány a budapesti fine dining éttermek szöveges vendégértékeléseinek témáit elemzi a BERTopic, egy neurális témamodellezési módszer, segítségével. A tanulmány 10.962 angol nyelvű, a Tripadvisorról származó, 2007 és 2024 márciusa között gyűjtött értékelést elemez. A hagyományos témamodellezési módszereknek korlátai vannak, különösen rövid szövegek esetében. A BERTopic a Sentence-BERT beágyazásokat kihasználva szemantikailag koherensebb témaazonosítást kínál. A vendégértékelések témamodellezése során 40 témát azonosítottunk, amelyek az éttermi szolgáltatás szinte minden aspektusát lefedik. Vizsgáltuk a számszerű vendégértékelések és az azonosított témák kapcsolatát, valamint azt, hogy az idő múlásával egyes témák aránya hogyan változott a véleményekben. A kutatás arra a következtetésre jutott, hogy bár a BERTopicnak vannak korlátai, ígéretesnek tűnik nagy mennyiségű szöveges adat elemzésében.
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