PACIS 2022 Proceedings

Paper Number

1282

Abstract

The presentation of online product reviews has been changing over the past decade. In addition to rating and texts, major electronic commerce platforms allow consumers to provide image-based reviews. Despite the prevalence, there is limited understanding towards the impacts of images in online reviews. This research aims to explore what information the review images bring and how such information affects the product sales. Drawing on the online review literature and cognitive theory of multimedia learning, we propose that the presence of review images bring product-related and product-unrelated information. Deep learning methods would be utilized to generate variables representing perceived product quality and product-unrelated information (i.e., human face number and face beauty) from the review images. Along with review text characteristics, we propose the perceived product quality and product-unrelated information from review images would influence the product sales directly and indirectly.

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