How Opinions are Received by Online Communities: A Case Study on Amazon.Com Helpfulness Votes

WWW (the 18th International World Wide Web Conference), pp. 141-150, 2009

10 Pages Posted: 16 Jan 2011

See all articles by Cristian Danescu-Niculescu-Mizil

Cristian Danescu-Niculescu-Mizil

Cornell University - Computing and Information Science

Gregory Kossinets

Google Inc.

Jon Kleinberg

Cornell University - Department of Computer Science

Lillian Lee

Cornell University - Department of Computer Science

Date Written: April 20, 2009

Abstract

There are many on-line settings in which users publicly express opinions. A number of these offer mechanisms for other users to evaluate these opinions; a canonical example is Amazon.com, where reviews come with annotations like "26 of 32 people found the following review helpful.'' Opinion evaluation appears in many off-line settings as well, including market research and political campaigns. Reasoning about the evaluation of an opinion is fundamentally different from reasoning about the opinion itself: rather than asking, "What did Y think of X?'', we are asking, "What did Z think of Y's opinion of X?'' Here we develop a framework for analyzing and modeling opinion evaluation, using a large-scale collection of Amazon book reviews as a dataset. We find that the perceived helpfulness of a review depends not just on its content but also but also in subtle ways on how the expressed evaluation relates to other evaluations of the same product. As part of our approach, we develop novel methods that take advantage of the phenomenon of review "plagiarism'' to control for the effects of text in opinion evaluation, and we provide a simple and natural mathematical model consistent with our findings. Our analysis also allows us to distinguish among the predictions of competing theories from sociology and social psychology, and to discover unexpected differences in the collective opinion-evaluation behavior of user populations from different countries.

Keywords: helpfulness, opinions, amazon, reviews, variance

Suggested Citation

Danescu-Niculescu-Mizil, Cristian and Kossinets, Gregory and Kleinberg, Jon and Lee, Lillian, How Opinions are Received by Online Communities: A Case Study on Amazon.Com Helpfulness Votes (April 20, 2009). WWW (the 18th International World Wide Web Conference), pp. 141-150, 2009. Available at SSRN: https://ssrn.com/abstract=1739947

Cristian Danescu-Niculescu-Mizil

Cornell University - Computing and Information Science ( email )

Ithaca, NY
United States

Gregory Kossinets

Google Inc. ( email )

1600 Amphitheatre Parkway
Second Floor
Mountain View, CA 94043
United States

Jon Kleinberg

Cornell University - Department of Computer Science ( email )

4130 Upson Hall
Ithaca, NY 14853-7501
United States

Lillian Lee (Contact Author)

Cornell University - Department of Computer Science ( email )

4130 Upson Hall
Ithaca, NY 14853-7501
United States

HOME PAGE: http://www.cs.cornell.edu/home/llee

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