Towards online anti-opinion spam: Spotting fake reviews from the review sequence

Author

Yuming Lin ; Tao Zhu ; Hao Wu ; Jingwei Zhang ; Xiaoling Wang ; Aoying Zhou

Author_Institution

Guangxi Key Lab. of Trusted Software, Guilin Univ. of Electron. Technol., Guilin, China

fYear

2014

fDate

17-20 Aug. 2014

Firstpage

261

Lastpage

264

Abstract

Detecting review spam is important for current e-commerce applications. However, the posted order of review has been neglected by the former work. In this paper, we explore the issue on fake review detection in review sequence, which is crucial for implementing online anti-opinion spam. We analyze the characteristics of fake reviews firstly. Based on review contents and reviewer behaviors, six time sensitive features are proposed to highlight the fake reviews. And then, we devise supervised solutions and a threshold-based solution to spot the fake reviews as early as possible. The experimental results show that our methods can identify the fake reviews orderly with high precision and recall.

Keywords

Internet; electronic commerce; unsolicited e-mail; e-commerce applications; fake review detection; online antiopinion spam; review sequence; review spam detection; supervised solutions; threshold-based solution; Decision support systems; review analysis; review spam; reviewer behavior;

fLanguage

English

Publisher

ieee

Conference_Titel

Advances in Social Networks Analysis and Mining (ASONAM), 2014 IEEE/ACM International Conference on

Conference_Location

Beijing

Type

conf

DOI

10.1109/ASONAM.2014.6921594

Filename

6921594