Inconsistency Investigation between Online Review Content and Ratings

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dc.contributor.authorShan, Guohou
dc.contributor.authorZhang, Dongsong
dc.contributor.authorZhou, Lina
dc.contributor.authorSuo, Lingge
dc.contributor.authorLim, Jaewan
dc.contributor.authorShi, Chunming
dc.date.accessioned2018-09-05T17:10:26Z
dc.date.available2018-09-05T17:10:26Z
dc.date.issued2018-08-16
dc.descriptioneBusiness and eCommerce Digital Commerce (SIGeBIZ), 2018en_US
dc.description.abstractDespite the tremendous role of online consumer reviews (OCRs) in facilitating consumer purchase decision making, the potential inconsistency between product ratings and review content could cause the uncertainty and confusions of prospect consumers toward a product. This research is aimed to investigate such inconsistency so as to better assist potential consumers with making purchase decisions. First, this study extracted a reviewer’s sentiments from review text via sentiment analysis. Then, it examined the correlation and inconsistency between product ratings and review sentiments via Pearson correlation coefficients (PCC) and box plots. Next, we compared such inconsistency patterns between fake and authentic reviews. Based on an analysis of 24,539 Yelp reviews, we find that although the ratings and sentiments are highly correlated, the inconsistency between the two is more salient in fake reviews than in authentic reviews. The comparison also reveals different inconsistency patterns between the two types of reviews.en_US
dc.description.sponsorshipThis research was partially supported by the National Science Foundation under Grants SES-1527684 and CNS-1704800. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the above funding agency.en_US
dc.format.extent10 PAGESen_US
dc.genrejournal articlesen_US
dc.identifierdoi:10.13016/M2K35MH6X
dc.identifier.citationGuohou Shan, Dongsong Zhang, Lina Zhou, Lingge Suo, Jaewan Lim, Chunming Shi, eBusiness and eCommerce Digital Commerce (SIGeBIZ), 2018en_US
dc.identifier.urihttp://hdl.handle.net/11603/11228
dc.language.isoen_USen_US
dc.publisherAISen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please contact the author.
dc.subjectOnline Customer Review (OCR)en_US
dc.subjectSentiment Analysisen_US
dc.subjectPearson correlation coefficients (PCC)en_US
dc.subject.otheronline consumer reviews
dc.subject.otherconsumer purchase decision making
dc.subject.otherinconsistency between product ratings and review content
dc.subject.othersentiment analysis
dc.subject.otherPearson correlation coefficients
dc.subject.otherbox plots
dc.subject.otherfake reviews
dc.subject.otherauthentic reviews
dc.titleInconsistency Investigation between Online Review Content and Ratingsen_US
dc.typeTexten_US

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