Research Information System
IET SOFTWARE, vol.11, no.3, pp.89-92, 2017 (SCI-Expanded)
In recent years, due to significant developments in online shopping and the widespread use of e-commerce, competition among companies has increased considerably. As a result, product reviews have become a primary factor in consumers' decision making, which has given rise to a market for fraudulent reviews about real products and services. In this study, the authors propose a model using a multiple classifier system to identify deceptive negative customer reviews, which they validated with a dataset of hotel reviews from TripAdvisor. The proposed model used five classifiers by following the majority voting combination rule - namely, libLinear, libSVM, sequential minimal optimisation, random forest, and J48 - the first two of which represent different implementations of support vector machines. Ultimately, the model provided remarkable results that demonstrate improvement upon approaches reported in the literature.