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Computing and using reputations for internet ratings
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Source Electronic Commerce archive
Proceedings of the 3rd ACM conference on Electronic Commerce table of contents
Tampa, Florida, USA
Pages: 154 - 162  
Year of Publication: 2001
ISBN:1-58113-387-1
Authors
Mao Chen  Princeton University, Princeton, NJ
Jaswinder Pal Singh  Princeton University, Princeton, NJ
Sponsor
SIGEcom: ACM Special Interest Group on Electronic Commerce
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 12,   Downloads (12 Months): 84,   Citation Count: 14
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ABSTRACT

Ratings for products and services are increasingly important on the Internet, as they allow users to harvest the wisdom of the community in making decisions. However, the difficulty with ratings is that little is known about the people providing them. Interpreting ratings well requires that the reputations of raters be factored into the scores computed for rated objects, even though these reputations are not explicitly available. Taking advantage of the insight that reputation can be computed implicitly from ratings, this paper addresses the reputation problem for raters and its application to evaluating rated objects. We develop a general method to automatically compute reputations for raters based on the ratings they and others give to objects, and incorporate these reputations to generate value-added information about rated objects. We evaluate our mechanisms by performing experiments on data from major rating sites, and show that they have the desired properties of a good reputation system. In the process, we analyze some key characteristics of different types of Internet ratings. To our knowledge, this is the first investigation into automatically computing raters'reputations and applying these reputations to better evaluate rated objects.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Arkin, H. and Colton, R. R. Statistical Methods, 5th edition, Barnes & Noble, Inc., 1970.
 
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Guernsey, L. Suddenly, Everybody's an Expert on Everything. The New York Times, Feb. 03, 2000.
 
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Hafner, K. Web Sites Begin to Self Organize. The New York Times, Jan. 18, 2001.
 
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CITED BY  14

Collaborative Colleagues:
Mao Chen: colleagues
Jaswinder Pal Singh: colleagues