Review Helpfulness Prediction: Survey

Online reviews have become the major driving factor influencing purchasing behavior and patterns of social customers. However, it is difficult for customer to cover good reviews about any product or service according to massive amount of reviews latest years. Many previous researches provide innovative models about predicting review helpfulness in E-commerce websites. Some of these studies exploring the direct effect of review attributes on review helpfulness while others focused on reviewer’s attributes only. The main objective of this research is to review the most important attributes that have an affect on review helpfulness from many perspectives such as datasets, techniques, frameworks and evaluation methods of the experiments. The paper ends up with important findings about most attributes effect the review helpfulness such as Review Valence.

Authors

Publication Details

Journal
Periodicals of Engineering and Natural Sciences (PEN)
Published
2025-12-31
DOI
https://doi.org/10.21533/pen.v7.i1.1511
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
0.00
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article

Review Helpfulness Prediction: Survey

Yasamyian Almutairi, Manal Abdullah, Dimah Alahmadi
Periodicals of Engineering and Natural Sciences (PEN)
Digital Marketing and Social Media
article

Review Helpfulness Prediction: Survey

Yasamyian Almutairi, Manal Abdullah, Dimah Alahmadi
article en

Abstract

Online reviews have become the major driving factor influencing purchasing behavior and patterns of social customers. However, it is difficult for customer to cover good reviews about any product or service according to massive amount of reviews latest years. Many previous researches provide innovative models about predicting review helpfulness in E-commerce websites. Some of these studies exploring the direct effect of review attributes on review helpfulness while others focused on reviewer’s attributes only. The main objective of this research is to review the most important attributes that have an affect on review helpfulness from many perspectives such as datasets, techniques, frameworks and evaluation methods of the experiments. The paper ends up with important findings about most attributes effect the review helpfulness such as Review Valence.

Periodicals of Engineering and Natural Sciences (PEN)Vol. 7(1)
Openalex Percentile: Top 21%
Digital Marketing and Social Media
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