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Analyzing Amazon CD Reviews with Bayesian Monitoring and Machine Learning Methods

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Date
2020
Author
Su, Eric
Advisor
Banks, David
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Abstract

This paper analyzes customer reviews of CDs sold on Amazon.com using various statistical and machine learning methods. We investigated the distribution properties through exploratory analyses and the Bayesian monitoring method was utilized to analyze life cycles of CDs. We proposed an adjustment to the classic Bayesian monitoring technique which allows it to deal with extreme changes in data. To predict how many reviews CDs get, we compared the performances of a range of machine learning models and identified important features affecting the number of reviews using permutation importance.

Description
Master's thesis
Type
Master's thesis
Department
Statistical Science
Subject
Statistics
Permalink
https://hdl.handle.net/10161/20776
Citation
Su, Eric (2020). Analyzing Amazon CD Reviews with Bayesian Monitoring and Machine Learning Methods. Master's thesis, Duke University. Retrieved from https://hdl.handle.net/10161/20776.
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.

Rights for Collection: Masters Theses


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