Skip navigation
Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01m613mx76j
Full metadata record
DC FieldValueLanguage
dc.contributor.advisorNarayanan, Arvind-
dc.contributor.authorGold, Sebastian-
dc.date.accessioned2014-07-17T19:27:46Z-
dc.date.available2014-07-17T19:27:46Z-
dc.date.created2014-05-
dc.date.issued2014-07-17-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01m613mx76j-
dc.description.abstractData collected from Amazon.com, reviews and product details, is used to explore various questions. Does a higher list price increase sales for a product? Do better reviews directly increase sales? Are reviewers influenced by other reviews? These subjects have been studied extensively, primarily through controlled experiments. For example, experiments have aimed to reveal higher advertised reference prices affect a consumer’s purchase decisions. We aim to create a framework and dataset that can be used to investigate correlations between various product properties and outcomes. Amazon.com was chosen because of the wealth of reviews, with review author tags, and also product metadata such as sales ranking. This data was collected for the present as well as several points in the past and was analyzed for patterns pertaining to the questions at handen_US
dc.format.extent20 pages*
dc.language.isoen_USen_US
dc.titleBEHAVIORAL SHOPPING: ANALYSIS OF CONSUMER BEHAVIOR THROUGH AMAZON PRODUCT LISTINGSen_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2014en_US
pu.departmentComputer Scienceen_US
pu.pdf.coverpageSeniorThesisCoverPage-
Appears in Collections:Computer Science, 1988-2020

Files in This Item:
File SizeFormat 
Sebastin_Gold_Thesis_2014.pdf6.18 MBAdobe PDF    Request a copy


Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.