Effects of Affective Language on Perceived Helpfulness of Online Reviews

Online communities that give their members the opportunity to rate and review products and services, like Yelp, Trip Advisor, Epinions, are highly valuable in helping consumers navigate through the unlimited volume of information they have access to. More positive ratings and reviews of a product or a service mean that more consumers are happy with that product or service, which through the influence of the reviews translates into increased commercial performance (Archak, Ghose, & Ipeirotis, 2011; Ludwig et al., 2013; Sonnier, McAlister, & Rutz, 2011). Online reviews are also useful to inform commercial marketing research and competitive intelligence (Lee & BradLow, 2011; Netzer, Feldman, Goldenberg, & Fresko, 2012). The reviews that have the greatest influence on consumer behavior are probably those that consumers themselves consider most helpful. What then makes a review helpful? Past studies have examined various features of the review texts (O’Mahony & Smyth, 2010), features of review authors (Liu & Park, 2015), and features of the reviewed objects (Bakhshi, Kanuparthy, & Shamma, 2015; Ghenai & Lizotte, 2015). In this research we investigate the effect of elements of affective language – positive and negative – of online reviews on their perceived helpfulness. On the one hand, we know that people naturally focus on positive, rather than negative things (Augustine, Mehl, & Larsen, 2011; Boucher & Osgood, 1969; Dodds et al., 2015). On the other hand, some studies suggest that negative words carry more information than positive ones (Garcia, Garas, & Schweitzer, 2012). Given these conflicting findings, whether and how use of positive words and use of negative words influence perceived helpfulness of evaluative textual units is an open question.