How to count thumb-ups and thumb-downs?: an information retrieval approach to user-rating based ranking of items

Authors:
Dell Zhang;Robert Mao;Haitao Li;Joanne Mao
Affiliations:
Birkbeck, University of London, London, United Kingdom;Microsoft Research, Redmond, WA, USA;Microsoft Corporation, Redmond, WA, USA;Hughes Network Systems, Germantown, MD, USA
Venue:
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Year:
2011

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Abstract

It is a common practice among Web 2.0 services to allow users to rate items on their sites. In this paper, we first point out the flaws of the popular methods for user-rating based ranking of items, and then argue that two well-known Information Retrieval (IR) techniques, namely the Probability Ranking Principle and Statistical Language Modelling, provide a simple but effective solution to this problem.