Examining the relationship between specific negative emotions and the perceived helpfulness of online reviews. Issue 4 (July 2019)

• Record Type: Journal Article
• Authors: Ren, Gang; Hong, Taeho
• Is Part Of: Information processing & management. Volume 56:Issue 4(2019:Jul.)
• Page Start: 1425
• Page End: 1438
• Publication Date: 2019-07
• Subjects: Negative emotions -- Review helpfulness -- Emotion classification -- Online reviews -- Text mining -- Product type; Information storage and retrieval systems -- Periodicals; Information science -- Periodicals; Systèmes d'information -- Périodiques; Sciences de l'information -- Périodiques; Information science; Information storage and retrieval systems; Periodicals; 658.4038
• DOI: 10.1016/j.ipm.2018.04.003
• Languages: English
• ISSNs: 0306-4573

Abstract

Abstract: This paper extracted discrete emotions from online reviews based on an emotion classification approach, and examined the differential effects of three discrete emotions (anger, fear, sadness) on perceived review helpfulness. We empirically tested the hypotheses by analyzing the "verified purchase" reviews on Amazon.com. The findings of this study extend the previous research by suggesting that product type moderates the effects of emotions on perceived review helpfulness. Anger embedded in a customer review exerts a greater negative impact on perceived review helpfulness for experience goods than for search goods. Fear embedded in a review is identified as an important emotional cue to positively affect the perceived review helpfulness with more persuasive messages. As the level of sadness embedded in a review increases, perceived review helpfulness decreases. These findings contribute to a better understanding of the important role of emotions embedded in reviews on the perceived review helpfulness. This study also provides practical insights related to the presentation of online reviews and gives suggestions for consumers regarding how to select and write a helpful review.