How Do Expressed Emotions Affect the Helpfulness of a Product Review? Evidence from Reviews Using Latent Semantic Analysis
Shimi Naurin Ahmad and Michel Laroche
International Journal of Electronic Commerce,
Volume 20, Number 1, Fall 2015, pp. 76-111.
Abstract:
Customers often search online for product reviews to make an informed buying decision. People write about their experience with the product in a review that often expresses a variety of emotions. How these emotions affect the helpfulness of the review is an intriguing but insufficiently studied question. Do discrete emotions have differential informational value in this case? Here, we build on cognitive appraisal theory to examine how discrete emotions (e.g., hope, happiness, anxiety, and disgust) embedded in the reviews affect the helpfulness votes of potential customers. We hypothesize that reviews where emotions associated with certainty are expressed will have a positive effect on review helpfulness and vice versa, regardless of their valence. Moreover, certainty mediates this effect. We adopted a quantitative content analysis approach (latent semantic analysis or LSA) to measure emotional content in these reviews. Findings demonstrate that discrete emotions have differential effects on the helpfulness of the reviews. The paper contributes to the better understanding of framing effects of discrete emotions.
Key Words and Phrases: Cognitive appraisal theory, emotions in online reviews, helpfulness of online reviews, latent semantic analysis, online word of mouth, online reviews.