Date of Award

2017

Document Type

Dissertation/Thesis

Submission Date

October 2026

Thesis/Dissertation Advisor [Chair]

Nur-tegin, Kanybek

Abstract

Online reviews play an important role in contemporary society, having been used to predict market trends and influence industry changes. In addition, many consumers depend on online reviews when deciding which products to buy. Recently, a large group of online venders have started incentivizing shoppers by providing product discounts in exchange for reviews. Some researchers believe that reviewers who are compensated for writing reviews will publish higher-than-average reviews, which may diminish the overall usefulness of online reviews as genuine predictors of product quality and purchaser satisfaction. First, this paper establishes a method for differentiating and isolating incentivized reviews. Then, this paper analyzes incentivized reviews to determine if they are in fact inflated, compared to nonincentivized reviews. Finally, a few methods are discussed for combating incentivized review bias in order to preserve the usefulness of online reviews as a predictive tool.

Comments

Includes bibliography.

Extent

51 p.

Identifier

FA00012614

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