On the volatility of online ratings: An empirical study

Christopher S. Leberknight, Soumya Sen, Mung Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

Many online rating systems represent product quality using metrics such as the mean and the distribution of ratings. However, the mean usually becomes stable as reviews accumulate, and consequently, it does not reflect the trend emerging from the latest user ratings. Additionally, understanding whether any variation in the trend is truly significant requires accounting for the volatility of the product's rating history. Developing better rating aggregation techniques should focus on quantifying the volatility in ratings to appropriately weight or discount older ratings. We present a theoretical model based on stock market metrics, known as the Average Rating Volatility (ARV), which captures the fluctuation present in these ratings. Next, ARV is mapped to the discounting factor for weighting (aging) past ratings and used as the coefficient in Brown's Simple Exponential Smoothing to produce an aggregate mean rating. This proposed method represents the "true" quality of a product more accurately because it accounts for both volatility and trend in the product's rating history. Empirical findings on rating volatility for several product categories using data from Amazon further motivate the need and applicability of the proposed methodology.

Original languageEnglish (US)
Title of host publicationE-Life
Subtitle of host publicationWeb-Enabled Convergence of Commerce, Work, and Social Life - 10th Workshop on E-Business, WEB 2011, Revised Selected Papers
PublisherSpringer Verlag
Pages77-86
Number of pages10
Volume108 LNBIP
ISBN (Print)9783642298721
DOIs
StatePublished - Jan 1 2012
Event10th Workshop on E-Business on E-Life: Web-Enabled Convergence of Commerce, Work, and Social Life, WEB 2011 - Shanghai, China
Duration: Dec 4 2011Dec 4 2011

Publication series

NameLecture Notes in Business Information Processing
Volume108 LNBIP
ISSN (Print)1865-1348

Other

Other10th Workshop on E-Business on E-Life: Web-Enabled Convergence of Commerce, Work, and Social Life, WEB 2011
CountryChina
CityShanghai
Period12/4/1112/4/11

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Management Information Systems
  • Business and International Management
  • Information Systems
  • Modeling and Simulation
  • Information Systems and Management

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    Leberknight, C. S., Sen, S., & Chiang, M. (2012). On the volatility of online ratings: An empirical study. In E-Life: Web-Enabled Convergence of Commerce, Work, and Social Life - 10th Workshop on E-Business, WEB 2011, Revised Selected Papers (Vol. 108 LNBIP, pp. 77-86). (Lecture Notes in Business Information Processing; Vol. 108 LNBIP). Springer Verlag. https://doi.org/10.1007/978-3-642-29873-8-8