Visual detection of singularities in review platforms
Alessandro Colantonio, Roberto Di Pietro, Marinella Petrocchi, Angelo Spognardi · 2015
Product and service reviews can markedly influence consumer purchase decisions, leading to financial gains or losses for businesses. Therefore, there is a growing interest towards techniques for bringing out reviews that could negatively or positively bias new customers. To this goal, we propose a visual analysis of reviews that enables quick elicitation of interesting patterns and singularities. The proposed approach is based on a theoretically sound framework, while its effectiveness and viability is demonstrated by its application to real data extracted from Tripadvisor and Booking.com.