Encyclopedia of Social Network Analysis and Mining

2018 Edition
| Editors: Reda Alhajj, Jon Rokne

Identifying Spam in Reviews

  • Zhiang WuEmail author
  • Lu Zhang
  • Youquan Wang
  • Jie Cao
Reference work entry
DOI: https://doi.org/10.1007/978-1-4939-7131-2_110200

Synonyms

Glossary

Features

A set of attributes indicating the spamming behavior

Review Spammer

A malicious user who write fraudulent reviews

Spam Detection

Identify spam reviews, users, or groups

Spam Review

A deceptive review to manipulate the opinon about the product

Water Army

A group of ghostwriters paid to post fake reviews

Definition

The fake reviews target at promoting or demoting the sale of products in e-commerce sites, and attracting attention or triggering curiosity in social networking sites, by creating and spreading purposeful comments. Hence, the goal of spam detection is to identify spam objects, including review/opinion spam, spam users, and spammer groups, from reviews.

Introduction

Online reviews are actually a kind of user-generated content (UGC) and hence provide a voice for customers to praise or criticize products,...

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Notes

Acknowledgment

This work was partially supported by the National Key Research and Development Program of China (2017YFD0401001), the National Natural Science Foundation of China (71571093, 91646204, 71372188), National Center for International Joint Research on E-Business Information Processing (2013B01035), Industry Projects in Jiangsu S&T Pillar Program (BE2014141), and Key/Surface Projects of Natural Science Research in Jiangsu Provincial Colleges and Universities (14KJA520001, 15KJB520012 and 15KJB520011).

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Copyright information

© Springer Science+Business Media LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Jiangsu Provincial Key Laboratory of E-BusinessNanjing University of Finance and EconomicsNanjingChina

Section editors and affiliations

  • Guandong Xu
    • 1
  • Peng Cui
    • 2
  1. 1.University of Technology SydneySydneyAustralia
  2. 2.Tsinghua UniversityBeijingChina