NDLI: Modeling and Predicting the Helpfulness of Online Reviews

Content Provider	IEEE Xplore Digital Library
Author	Yang Liu Xiangji Huang Aijun An Xiaohui Yu
Copyright Year	2008
Description	Author affiliation: Sch. of Inf. Technol., York Univ., Toronto, ON (Xiangji Huang; Xiaohui Yu) \|\| Dept. of Comput. Sci. & Eng., York Univ., Toronto, ON (Yang Liu; Aijun An)
Abstract	Online reviews provide a valuable resource for potential customers to make purchase decisions. However, the sheer volume of available reviews as well as the large variations in the review quality present a big impediment to the effective use of the reviews, as the most helpful reviews may be buried in the large amount of low quality reviews. The goal of this paper is to develop models and algorithms for predicting the helpfulness of reviews, which provides the basis for discovering the most helpful reviews for given products. We first show that the helpfulness of a review depends on three important factors: the reviewerpsilas expertise, the writing style of the review, and the timeliness of the review. Based on the analysis of those factors, we present a nonlinear regression model for helpfulness prediction. Our empirical study on the IMDB movie reviews dataset demonstrates that the proposed approach is highly effective.
Starting Page	443
Ending Page	452
File Size	352912
Page Count	10
File Format	PDF
ISBN	9780769535029
ISSN	15504786
DOI	10.1109/ICDM.2008.94
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-15
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Predictive models Voting Writing Motion pictures Impedance Data mining Computer science Data engineering Information technology Prediction algorithms Helpfulness prediction Review mining
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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