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.


    Access

    Download

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Exploring thematic composition of online reviews: A topic modeling approach


    Contributors:

    Published in:

    Publication date :

    2020




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    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

    Free access

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

    Metti Detricia Pratiwi / Ken Ditha Tania | DOAJ | 2025

    Free access

    Exploring the Relationship Between Topic Area Knowledge and Forecasting Performance

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


    Tracing the evolution of service robotics: Insights from a topic modeling approach

    Ott, Ingrid / Savin, Ivan / Konop, Chris | BASE | 2021

    Free access