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Electronic commerce (e-commerce) has unquestionably become an indispensable part of our lives. However, effectively eliminating the in-built risks and uncertainty in e-commerce remains a challenge to many businesses. In general, customer reviews are provided to strengthen information transparency about products/services and mitigate related risks and uncertainty during a purchasing process. Many researchers already noticed the effect of customer reviews in this regard; however, the majority of the discussions so far are primarily centered on the characteristics related to either reviews themselves or the products under scrutiny (or both). For example, substantial studies found that the characteristics of reviews such as average ratings (Jiang & Wang, 2008), dispersion of ratings (Zhu & Zhang, 2010), review valence (Clemons, Gao, & Hitt, 2006), review quantity (Chevalier & Mayzlin, 2006), etc. play a role in consumers’ decision making. These factors have been, with varying degrees of success, shown to play a role in product sales growth, price premium and so on. Other factors, which have also been mentioned, are more related to products themselves, such as product quality (Jiang & Wang, 2008), product price (Ghose & Ipeirotis, 2010), product age (Hu, Liu, & Zhang, 2008), product popularity (Zhu & Zhang, 2010).
Beyond this, there is another stream of research which is focused more on semantic patterns embedded within customer reviews. For example, Ong et al. state that shill reviews (fake or manipulated reviews) created to manipulate the reputation of products are prone to have more official features per sentence, a higher percentage of sentences containing official features, and less readability (Ong, Mannino, & Gregg, 2014). Tian et al. demonstrate a refined classification scheme to deal with sentiments expressed in product reviews (Tian et al., 2016). Ahmad and Laroche found that the emotions expressed in reviews may influence people’s perception of the helpfulness of such reviews (Ahmad & Laroche, 2015). For example, the hope expressed in the reviews may have a negative effect, and happiness may have a positive effect.
In this study, we are specifically interested in the emotions that are revealed in the comments of seller reviews, which are technically more related to the performance of sellers (seller reviews as opposed to product reviews) and their associated impact on prospective buyers’ trust. Many studies show trust can be transferred from one entity to another; and this sort of trust transference is viewed as one of the effective strategies to develop trust (Lim, Sia, Lee, & Benbasat, 2006). That is, when a consumer trusts a popular web portal such as eBay or Amazon, he will tend to trust sellers affiliated with the portal based solely on the reputation of that web portal (Lim et al., 2006). Cheung and Lee validated this positive relationship between trust belief and purchase intention (Cheung & Lee, 2008). Pavlou and Dimoka find a similar positive correlation between trust and price premium (Pavlou & Dimoka, 2006). On these grounds, we assume that if a consumer trusts a seller, he/she will trust this seller’s products as well. Consequently, we believe that the trust feeling expressed in seller reviews can influence consumers’ impressions about their products. This premise provides the rationale for our study.