Exploring thematic composition of online reviews: A topic modeling approach
Vamsi Vallurupalli () and
Indranil Bose ()
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Vamsi Vallurupalli: Indian Institute of Management Calcutta
Indranil Bose: Indian Institute of Management Calcutta
Electronic Markets, 2020, vol. 30, issue 4, No 9, 804 pages
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.
Keywords: Latent Dirichlet allocation; Online reviews; Review influence; Thematic content; Topic modeling; Yelp (search for similar items in EconPapers)
JEL-codes: M31 (search for similar items in EconPapers)
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