Modeling and Prediction of Online Product Review Helpfulness: A Survey

Gerardo Ocampo Diaz and Vincent Ng.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, pp. 698-708, 2018.

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Abstract

As the popularity of free-form usergenerated reviews in e-commerce and review websites continues to increase, there is a growing need for automatic mechanisms that sift through the vast number of reviews and identify quality content. Online review helpfulness modeling and prediction is a task which studies the factors that determine review helpfulness and attempts to accurately predict it. This survey paper provides an overview of the most relevant work on product review helpfulness prediction and understanding in the past decade, discusses gained insights, and provides guidelines for future research.

BibTeX entry

@InProceedings{Ocampo+Ng:18a,
  author = {Ocampo Diaz, Gerardo and Vincent Ng},
  title = {Modeling and Prediction of Online Product Review Helpfulness: A Survey},
  booktitle = {Proceedings of 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  pages = {698--708}, 
  year = 2018}