Ngo-Ye and Sinha (2014) developed a text regression model for predicting the helpfulness of 7,465 online restaurant reviews posted at Yelp.com and 584 book reviews posted at Amazon.com. According to the authors, most review opinion mining studies focused on sentiment rather than quality and ignored reviewer engagement characteristics. The authors argued that reviewer characteristics influence the perception of helpfulness and that decision makers at online organizations who rely on user-generated content to gain marketing advantage could better leverage that content if they understood what makes it helpful to others and if they could predict that helpfulness.