Abstract Online reviews are a critical component of the retail business ecosystem today. They help consumers share feedback and readers make informed choices. As such, it is important to understand the mechanism driving the creation of reviews and identify factors which make them useful for readers. Extant work in this field has largely ignored the distribution of thematic content in reviews and its role in review diagnosticity. This article attempts to bridge the gap. A novel approach is proposed to explore the distribution of thematic content in reviews, in terms of underlying topics, and test its impact on influence of reviews. The approach is illustrated through a case study using data from Yelp. Implications of the study for theory and practice are discussed.


    Zugriff

    Download

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Exploring thematic composition of online reviews: A topic modeling approach


    Beteiligte:

    Erschienen in:

    Electronic Markets ; 30 , 4 ; 791-804


    Erscheinungsdatum :

    2020




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    BKL:    85.40 Marketing / 83.72 Verkehrswirtschaft



    Exploring the Citywide Human Mobility Patterns of Taxi Trips through a Topic-Modeling Analysis

    Hui Xiong / Kaiqiang Xie / Lu Ma et al. | DOAJ | 2021

    Freier Zugriff

    Knowledge Discovery Through Topic Modeling on GoPartner User Reviews Using BERTopic, LDA, and NMF

    Metti Detricia Pratiwi / Ken Ditha Tania | DOAJ | 2025

    Freier Zugriff

    Exploring the Relationship Between Topic Area Knowledge and Forecasting Performance

    Miller, S.M. / Forlines, C. / Regan, J. | British Library Conference Proceedings | 2012



    Augmenting Topic Finding in the NASA Aviation Safety Reporting System using Topic Modeling

    Paradis, Carlos / Kazman, Rick / Davies, Misty et al. | AIAA | 2021