2018/07/29 by L. H. Nguyen, Long Hoang Nguyen, Nguyen, L. H. +6
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Sentiment Analysis and Opinion Mining #Spam and Phishing Detection #Text and Document Classification Technologies #cs.AI #cs.CL #cs.IR
paper · pdf · doi:10.48550/arxiv.1807.11024
15 pages, In Journal of Science, Special Issue: Natural Science and Technology, Ho Chi Minh City University of Education
arxiv created 2018/07/29 · openalex publication_date 2018/07/29 · arxiv updated 2018/07/31 · openalex created_date 2018/08/03 · openalex updated_date 2026/07/28
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.