A critical assessment of consumer reviews: A hybrid NLP-based methodology

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dc.authoridDursun Delen / 0000-0001-8857-5148en_US
dc.authorscopusidDursun Delen / 55887961100en_US
dc.authorwosidDursun Delen / AGA-9892-2022
dc.contributor.authorBiswas, Baidyanath
dc.contributor.authorSengupta, Pooja
dc.contributor.authorKumar, Ajay
dc.contributor.authorDelen, Dursun
dc.contributor.authorGupta, Shivam
dc.date.accessioned2022-06-07T07:01:22Z
dc.date.available2022-06-07T07:01:22Z
dc.date.issued2022en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Bölümüen_US
dc.description.abstractOnline reviews are integral to consumer decision-making while purchasing products on an e-commerce platform. Extant literature has conclusively established the effects of various review and reviewer related predictors towards perceived helpfulness. However, background research is limited in addressing the following problem: how can readers interpret the topical summary of many helpful reviews that explain multiple themes and consecutively focus in-depth? To fill this gap, we drew upon Shannon's Entropy Theory and Dual Process Theory to propose a set of predictors using NLP and text mining to examine helpfulness. We created four predictors - review depth, review divergence, semantic entropy and keyword relevance to build our primary empirical models. We also reported interesting findings from the interaction effects of the reviewer's credibility, age of review, and review divergence. We also validated the robustness of our results across different product categories and higher thresholds of helpfulness votes. Our study contributes to the electronic commerce literature with relevant managerial and theoretical implications through these findings. © 2022 Elsevier B.V.en_US
dc.identifier.citationBiswas, B., Sengupta, P., Kumar, A., Delen, D., & Gupta, S. (2022). A critical assessment of consumer reviews: A hybrid NLP-based methodology. Decision Support Systems, doi:10.1016/j.dss.2022.113799en_US
dc.identifier.doi10.1016/j.dss.2022.113799en_US
dc.identifier.issn0167-9236en_US
dc.identifier.scopus2-s2.0-85129723722en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.dss.2022.113799
dc.identifier.urihttps://hdl.handle.net/20.500.12713/2802
dc.identifier.wosWOS:000823389200005en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorDelen, Dursun
dc.language.isoenen_US
dc.publisherElsevier B.V.en_US
dc.relation.ispartofDecision Support Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectNatural Language Processing (NLP)en_US
dc.subjectOnline Reviewsen_US
dc.subjectShannon's Entropyen_US
dc.subjectText Analyticsen_US
dc.subjectZero-Truncated Regressionen_US
dc.titleA critical assessment of consumer reviews: A hybrid NLP-based methodologyen_US
dc.typeArticleen_US

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