Product review management software based on multiple classifiers


ÇATAL Ç., Guldan S.

IET SOFTWARE, vol.11, no.3, pp.89-92, 2017 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 11 Issue: 3
  • Publication Date: 2017
  • Doi Number: 10.1049/iet-sen.2016.0137
  • Journal Name: IET SOFTWARE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.89-92
  • Istanbul Kültür University Affiliated: Yes

Abstract

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.