Abstract
To allow consumers cast a vote on the helpfulness of an online review becomes a popular practice by many ecommerce companies. It was assumed this crowd-sourcing-method-generated ranking could help online shoppers quickly identify quality reviews for a popular product. However, through data collected from amazon.com, we found those most useful reviews identified through this method are heavily influenced by the order the reviews being submitted. Early reviews enjoy a first-mover advantage over later reviews via Matthew effect. How to remedy such influence is discussed.
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Wan, Y. (2013). The Matthew Effect in Online Review Helpfulness. In: Järveläinen, J., Li, H., Tuikka, AM., Kuusela, T. (eds) Co-created Effective, Agile, and Trusted eServices. ICEC 2013. Lecture Notes in Business Information Processing, vol 155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39808-7_4
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DOI: https://doi.org/10.1007/978-3-642-39808-7_4
Publisher Name: Springer, Berlin, Heidelberg
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