We propose a novel unsupervised extractive approach for summarizing online reviews by exploiting review helpfulness ratings. In addition to using the helpfulness ratings for review-level filtering, we suggest using them as the supervision of a topic model for sentence-level content scoring. The proposed method is metadata-driven, requiring no human annotation, and generalizable to different kin...

The purpose of this study is to propose a data mining approach to predict the helpfulness scores of online product reviewers. Such prediction can facilitate consumers to judge whether to believe or disbelieve reviews written by different reviewers and can help e-stores or third-party product review websites to target and retain quality reviewers. In this study, we identify eight independent var...

Using signaling theory, this study unpacked the mechanisms through which online review information quality and reviewer credibility influence helpfulness, in e-commerce context. Conducting a survey with users Danang having read reviews on Shopee.vn, 244 valid responses were used to evaluate research model via PLS-SEM software. The found that of strongly influences helpfulness compared previous ...

With the growing popularity of online user-generated reviews, research has emerged to understand the mechanism of how a review is voted helpful, focusing on the central-route influences of review content and quality, yet little research has studied the roles of peripheral cues such as reviewer credibility and contextual factors. Drawing on the theories of elaboration likelihood model and source...

In this work we investigate how the introduction of the Verified Purchase (VP) badge on Amazon.com affected both the review helpfulness and the product ratings. We first conduct a propensity score matching study and find that all else equal, camera reviews are on average ranked 7 positions higher than non-VP reviews, while book VP reviews are on average ranked 11 positions higher than non-VP re...

Most E-commerce web sites and online communities provide interfaces and platforms for consumers to express their opinions about a specific product by writing personal reviews. The fast development of E-commerce has caused such a huge amount of online product reviews to become available to consumers that it is impossible for potential consumers to read through all the reviews and to make a quick...

Abstract The purpose of this study is to explore the effect purchase context on relative importance drivers online review helpfulness and also psychological process behind it. This will help management team retailers create a better ranking system that considers context. Based theory helpful behavior, we propose review-helpfulness driven by characteristics such as diagnosticity vicarious expres...

Research Article Kevin K.Y. Kuan The University of Sydney [email protected] Kai-Lung Hui Hong Kong University of Science and Technology [email protected] Many online review systems adopt a voluntary voting mechanism to identify helpful reviews to support consumer purchase decisions. While several studies have looked at what makes an online review helpful (review helpfulness), little is known ...

Consumers frequently read online consumer reviews before purchasing products both online and offline (at stores). Yet, reviews are known to have certain biases. This paper surveys 17 types of biases that previous studies identified. The effects of these biases are intertwined and hard to isolate from one another. It is then difficult to assess the impact of each bias on how consumers rate the h...