Abstract

This paper build on 1 489194 product reviews from 30 product categories retrieved from Amazon.com. Product categories are classified by use of natural language analysis tools with computing of subjectivity scores reflecting a search/experience product dimension. Results show a distinct effect of self-selection where the average review score gradually decreases. For most products, no undershooting period was observed, even though a limited number of products groups had this development pattern. Review length, verified purchase and use of real names contributed to increasing helpfulness ratings. The results further suggest search products to be more influenced by review length than experience products.

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