Review Pollution: Pedagogy for a Post-Truth Society

Author:

West Emily

Abstract

Consumer reviews on platforms like Amazon are summarized into star ratings, used to weight search results, and consulted by consumers to guide purchase decisions. They are emblematic of the interactive digital environment that has purportedly transferred power from marketers to ‘regular people,’ and yet they represent the infiltration of promotional concerns into online information, as has occurred in search and social media content. Consumers’ ratings and reviews do promotional work for brands—not just for products but the platforms that host reviews—that money can’t always buy. Gains in power by consumers are quickly met with new strategies of control by companies who depend on reviews for reputational capital. Focusing on ecommerce giant Amazon, this article examines the complexities of online reviews, where individual efforts to provide product feedback and help others make choices become transformed into an information commodity and promotional vehicle. It acknowledges the ambiguous nature of reviews due to the rise of industries and business practices that influence or fake reviews as a promotional strategy. In response are yet other business practices and platform policies aiming to provide better information to consumers, protect the image of platforms that host reviews, and punish ‘bad actors’ in competitive markets. The complexity in the production, regulation, and manipulation of product ratings and reviews illustrates how the high stakes of attention in digital spaces create fertile ground for disinformation, which only emphasizes to users that they inhabit a ‘post-truth’ reality online.

Publisher

Cogitatio

Subject

Communication

Reference70 articles.

1. Amazeen, M. A., & Muddiman, A. R. (2018). Saving media or trading on trust? The effects of native advertising on audience perceptions of legacy and online news publishers. Digital Journalism, 6(2), 176–195.

2. Amazon. (2020a). Community guidelines. https://www.amazon.com/gp/help/customer/display.html/ref=hp_left_v4_sib?ie=UTF8&nodeId=GLHXEX85MENUE4XF

3. Amazon. (2020b). Customer reviews. https://www.amazon.com/gp/help/customer/display.html/ref=hp_left_v4_sib?ie=UTF8&nodeId=G3UA5WC5S5UUKB5G

4. Amazon. (2020c). How are product star ratings calculated? https://www.amazon.com/gp/help/customer/display.html/ref=hp_left_v4_sib?ie=UTF8&nodeId=GQUXAMY73JFRVJHE

5. Anderson, E. T., & Simester, D. I. (2014). Reviews without a purchase: Low ratings, loyal customers, and deception. Journal of Marketing Research, 51(3), 249–269.

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