The importance of online reviews in e-commerce cannot be overstated, but few studies have focused on user-generated photos (UGPs) in reviews, especially human faces in UGPs. In this study, using Amazon online review data, we divide online reviews into text with UGPs, UGPs with faces, and UGPs with multiple faces based on the presence and number of faces, and discuss their effects on review helpfulness. Drawing on media richness theory and emotional contagion effects, we argue that faces provide a richness of information that can increase the effectiveness of photos as information mediators. Moreover, we argue that facial expressions and emotional states, as read-in and read-out devices that convey individual emotions, affect other consumers\u27 perceived review helpfulness. This study contributes to the literature on online reviews, media richness theory, and emotional contagion effects, while providing practical insights for e-commerce sites and consumers seeking to write effective online reviews
