An Analysis of the Differential Impact of Reviews and Reviewers at Amazon.com

Online product review networks help to transmit information that customers can use to evaluate products in Internet commerce. These networks frequently include an explicit social component allowing consumers to view both how community members have rated individual product reviews and the social status of individual reviewers. We analyze how these social factors impact consumer responses to consumer review information. We use a new dataset collected from Amazon.com’s customer reviews of books. This dataset allows us to control for the degree to which other community members found the review helpful, and the reputation of the reviewer in the community. We find that more helpful reviews and highlighted reviews have a stronger impact on sales than other reviews do. We also find that reviewer information has a stronger impact on less popular books than on more popular books. These results suggest that the dynamics of reputation communities make it harder for self-interested parties to manipulate reviews versus an environment where all reviews are treated equally.

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