HelpMeter: A Nonlinear Model for Predicting the Helpfulness of Online Reviews

Author

Liu, Yang ; Huang, Xiangji ; An, Aijun ; Yu, Xiaohui

Author_Institution

Dept. of Comput. Sci. & Eng., York Univ., Toronto, ON

Volume

1

fYear

2008

fDate

9-12 Dec. 2008

Firstpage

793

Lastpage

796

Abstract

With the flourish of the Internet, online review mining has attracted a lot of attention from the research community. However, compared to various well-studied sentiment analysis and opinion summarization problems, less effort has been made to analyze the quality of online reviews. The objective of this paper is to fill in this gap by automatically evaluating the "helpfulness" of reviews and consequently developing novel models to identify the most helpful reviews for a particular product. In particular, based on a thorough analysis of various factors that may affect the review quality, we propose HelpMeter, a nonlinear regression model for helpfulness prediction. Some preliminary experiments were conducted on a movie review data set, and the performance results confirm the superiority of the proposed method.

Keywords

Internet; data mining; regression analysis; reviews; HelpMeter; Internet; helpfulness prediction; nonlinear model; nonlinear regression model; online reviews; opinion summarization problems; review quality; sentiment analysis; Blogs; Computer science; Filtering; Intelligent agent; Internet; Logistics; Motion pictures; Predictive models; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on

Conference_Location

Sydney, NSW

Print_ISBN

978-0-7695-3496-1

Type

conf

DOI

10.1109/WIIAT.2008.299

Filename

4740551