Opinion Spam Recognition Method for Online Reviews using Ontological Features
This addresses the problem of fake reviews misleading consumers and automated systems in e-commerce, though it appears incremental.
The paper tackles opinion spam detection in online reviews by proposing a knowledge-based ontology approach, achieving an accuracy higher than 75%.
Nowadays, there are a lot of people using social media opinions to make their decision on buying products or services. Opinion spam detection is a hard problem because fake reviews can be made by organizations as well as individuals for different purposes. They write fake reviews to mislead readers or automated detection system by promoting or demoting target products to promote them or to damage their reputations. In this paper, we pro-pose a new approach using knowledge-based Ontology to detect opinion spam with high accuracy (higher than 75%). Keywords: Opinion spam, Fake review, E-commercial, Ontology.