Research of Fraud Review Detection Model on O2O Platform

LI Jing; WU Guo-shi; XIE Fei; YAO Xu; QI Jia-yin; SUN Peng-fei

doi:10.3969/j.issn.0372-2112.2016.12.07

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Research of Fraud Review Detection Model on O2O Platform

更新时间：2025-07-16

- Research of Fraud Review Detection Model on O2O Platform
- Acta Electronica Sinica Vol. 44, Issue 12, Pages: 2855-2860(2016)
- 作者机构：
  
  1. 北京邮电大学软件学院,北京,100876
  2. 新华社通信技术局,北京,100803
  3. 北京邮电大学经济管理学院,北京,100876
  4. 北京邮电大学软件学院,北京,100876
  5. 新华社通信技术局,北京,100803
  6. 北京邮电大学经济管理学院,北京,100876
- 作者简介：
- 基金信息：
  
  National Program on Key Basic Research Project of China (973 Program) (No.2013CB329604);National Natural Science Foundation of China (No.71231002);National Natural Science Foundation of Beijing Municipality, China (No.9122018);Ph.D. Programs Foundation of Ministry of Education of China (No.20120005110015);713 Laboratory Technique Research Program of Xinhua News Agency--Big Data and Intelligent Information Processing Technology
- DOI：10.3969/j.issn.0372-2112.2016.12.07
  CLC： TP181
- Published Online：25 December 2016，
  
  Published：2016
- 稿件说明：
移动端阅览
LI Jing, WU Guo-shi, XIE Fei, et al. Research of Fraud Review Detection Model on O2O Platform[J]. Acta Electronica Sinica, 2016, 44(12): 2855-2860.
DOI：

LI Jing, WU Guo-shi, XIE Fei, et al. Research of Fraud Review Detection Model on O2O Platform[J]. Acta Electronica Sinica, 2016, 44(12): 2855-2860. DOI： 10.3969/j.issn.0372-2112.2016.12.07.

摘要

生活消费平台已成为人们获取商家信息、反馈服务或产品质量的重要平台.虚假评论作为一种夸大或诽谤目标商家口碑的商业行为在生活消费平台很普遍，具有很强的危害性.本文对某网站的真实评论展开虚假评论研究，深入分析研究虚假评论的特征，从可信度的角度出发，提出用户及商家可信度模型.利用评论人的行为特征、商家的特征和评论文本的特征构建了虚假评论识别模型，经测试该模型达到了一个良好的识别效果.

Abstract

Living-consumption platform has become a very important platform for customers to extract information of businesses

and view or submit comments on the quality of services or products.It is common that fake reviews

as a commercial activity

are used to exaggerate or damage the reputation of a target business

which is extremely harmful.This paper chose an O2O (Online To Offline) platform

from which reviews are derived

to study fake reviews.With an in-depth study on features of fake reviews

it raised the user-credibility and shop-credibility evaluation model respectively from the credibility perspective.Based on features of reviewers

businesses

and review texts

it established a fake review identification model

and through testing this model showed excellent performance in identification.

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