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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp0147429c88q
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dc.contributor.advisorWang, Mengdi-
dc.contributor.authorYin, Jennifer-
dc.date.accessioned2018-08-20T13:54:13Z-
dc.date.available2018-08-20T13:54:13Z-
dc.date.created2018-04-17-
dc.date.issued2018-08-20-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp0147429c88q-
dc.description.abstractThe rise of e-commerce in recent years has forced traditional retailers to change old business practices to keep up. In particular, many businesses have turned to big data in business analytics to keep up with changing consumer dynamics. Unsurprisingly, Amazon has reigned in both ecommerce and consumer analytics, accounting for 53% of the growth in US retail sales in 2017. To understand new consumer dynamics in a changing retail landscape, this thesis develops an analysis pipeline for Amazon products. Starting with the initial data collection, this pipeline scrapes the information for a product group and analyzes the reviews and ratings for each individual product to characterize consumer shopping trends for Amazon products.en_US
dc.format.mimetypeapplication/pdf-
dc.language.isoenen_US
dc.titleCounting Stars: A Pipeline for Amazon Consumer and Product Analytics with Case Studies in Discretionary Productsen_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2018en_US
pu.departmentOperations Research and Financial Engineeringen_US
pu.pdf.coverpageSeniorThesisCoverPage-
pu.contributor.authorid960962966-
Appears in Collections:Operations Research and Financial Engineering, 2000-2019

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