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

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dc.contributor.authorQiao, Zhilei
dc.contributor.authorZhang, Xuan
dc.contributor.authorZhou, Mi
dc.contributor.authorWang, Gang Alan
dc.contributor.authorFan, Weiguo
dc.date.accessioned2016-12-29T00:45:22Z
dc.date.available2016-12-29T00:45:22Z
dc.date.issued2017-01-04
dc.description.abstractOnline 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.extent10 pages
dc.identifier.doi10.24251/HICSS.2017.222
dc.identifier.isbn978-0-9981331-0-2
dc.identifier.urihttp://hdl.handle.net/10125/41376
dc.language.isoeng
dc.relation.ispartofProceedings of the 50th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectProduct defects
dc.subjectonline customer reviews
dc.subjecttext analysis
dc.subjectLDA
dc.subjectproduct quality
dc.titleA Domain Oriented LDA Model for Mining Product Defects from Online Customer Reviews
dc.typeConference Paper
dc.type.dcmiText

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