Abstract

Extant research has widely studied the impact of online product review on sales and most studies have found a significant impact of these reviews as an e-WOM tool. Given the importance of the online reviews, we study a hitherto understudied area of antecedents of sentiments in user reviews. We assess the impact of contagion effect of past review sentiments on reviewers' choice to write a review. We analyze the impact of emotional response of users while writing product reviews triggered by the appraisal response to prior online reviews. A short selection of reviews, which most e-commerce websites show, along with the numerical product rating (if any) could strongly bias the sentiments in a review being written under their influence. Through a mix of experimental methods and text analysis of online reviews, we find that review writers tend to veer towards extreme reviews in absence of any benchmark or prior reviews

Recommended Citation

Jha, A. & Shah, S. (2017). Influencing the Influencers: Analyzing Impact of Prior Review Sentiments on Product Reviews. In Paspallis, N., Raspopoulos, M. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Information Systems Development: Advances in Methods, Tools and Management (ISD2017 Proceedings). Larnaca, Cyprus: University of Central Lancashire Cyprus. ISBN: 978-9963-2288-3-6. http://aisel.aisnet.org/isd2014/proceedings2017/CogScience/4.

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Influencing the Influencers: Analyzing Impact of Prior Review Sentiments on Product Reviews

Extant research has widely studied the impact of online product review on sales and most studies have found a significant impact of these reviews as an e-WOM tool. Given the importance of the online reviews, we study a hitherto understudied area of antecedents of sentiments in user reviews. We assess the impact of contagion effect of past review sentiments on reviewers' choice to write a review. We analyze the impact of emotional response of users while writing product reviews triggered by the appraisal response to prior online reviews. A short selection of reviews, which most e-commerce websites show, along with the numerical product rating (if any) could strongly bias the sentiments in a review being written under their influence. Through a mix of experimental methods and text analysis of online reviews, we find that review writers tend to veer towards extreme reviews in absence of any benchmark or prior reviews