Perceived value of information sharing in online environments: User engagement and social reputation

Consumer reviews have received much attention both in academia and industry, since it has been found that they have significant effects on people's decision-making behaviors relating to online shopping or choosing services. The readers/visitors on various online communities where such reviews are posted evaluate the helpfulness of a review based on the extent to which the review is helpful in their information seeking and decision-making tasks. However, it is often not clear what makes a review useful to a reader. Several previous works have analyzed textual features relating to reviews to determine their usefulness, but given that most of these reviews are generated and shared through community-based or social media sites, the features that incorporate social features and social engagement could have an important role to play in making a review useful. The work described in this paper uses data available from Yelp, a social review and recommendation site, to build models that examine the impact of various features, including basic, reviewer's engagement, social reputation, and business type, based on the number of votes for helpfulness a review receives. Our findings suggest that reviewer's social contextual information (engagement and reputation) is influential in affecting perceived helpfulness of a review and improves the accuracy of prediction model. The findings also suggest that business type (restaurants vs. transportations) affects the ways in which consumers consider a review.