A Domain Oriented LDA Model for Mining Product Defects from Online Customer Reviews

dc.contributor.author Qiao, Zhilei
dc.contributor.author Zhang, Xuan
dc.contributor.author Zhou, Mi
dc.contributor.author Wang, Gang Alan
dc.contributor.author Fan, Weiguo
dc.date.accessioned 2016-12-29T00:45:22Z
dc.date.available 2016-12-29T00:45:22Z
dc.date.issued 2017-01-04
dc.description.abstract Online reviews provide important demand-side knowledge for product manufacturers to improve product quality. However, discovering and quantifying potential products’ defects from large amounts of online reviews is a nontrivial task. In this paper, we propose a Latent Product Defect Mining model that identifies critical product defects. We define domain-oriented key attributes, such as components and keywords used to describe a defect, and build a novel LDA model to identify and acquire integral information about product defects. We conduct comprehensive evaluations including quantitative and qualitative evaluations to ensure the quality of discovered information. Experimental results show that the proposed model outperforms the standard LDA model, and could find more valuable information. Our research contributes to the extant product quality analytics literature and has significant managerial implications for researchers, policy makers, customers, and practitioners.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2017.222
dc.identifier.isbn 978-0-9981331-0-2
dc.identifier.uri http://hdl.handle.net/10125/41376
dc.language.iso eng
dc.relation.ispartof Proceedings of the 50th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Product defects
dc.subject online customer reviews
dc.subject text analysis
dc.subject LDA
dc.subject product quality
dc.title A Domain Oriented LDA Model for Mining Product Defects from Online Customer Reviews
dc.type Conference Paper
dc.type.dcmi Text
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