# Opinion Spam Recognition Method for Online Reviews using Ontological Features

arXiv: https://arxiv.org/abs/1807.11024 · HTML: https://mlsanity.com/paper/1807.11024/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Jul 2018.

## Built on by (most cited first, 1 of 1)

- [Graph-Based Optimisation of Network Expansion in a Dockless Bike Sharing System](https://mlsanity.com/paper/2404.01320/) (2024)

## Abstract (arXiv)

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.