Cloud based Framework for Fake Review Detection

MD Towhidul Islam Robin

Cloud based Framework for Fake Review Detection

MD Towhidul Islam Robin * §

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§ Stamford University Bangladesh

Cloud based Framework for Fake Review Detection

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Abstract

Online reviews are one of the significant factors in a customer’s purchase decision or to avail of any service. Online reviews give rise to the potential threats that fake reviewers may write a false review to artificially promote a product or defaming value of a service. Using Natural Language Processing, many methods have already been developed to detect fake reviews, especially reviews written in the English language. In this paper, I propose a novel framework where authenticity of a feedback will check through two perspectives. Firstly, the system checks whether the review is fake or not. Secondly, it also checks the authenticity of the reviewer. The outcome result accumulates in cloud storage for providing further business analytics.

References

6 Cites in Article

Reference Format

Snehal Dixit,A Agrawal (2013). SURVEY ON REVIEW SPAM DETECTION.
M Ott,Y Choi,C Cardie,J Hancock (2011). Finding deceptive opinion spam by any stretch of the imagination.
N Jindal,B Liu (2007). Opinion spam and analysis.
Asa Hammad (2003). An extensive empirical study of feature selection metrics for text classification.
R Lau,S Liao,Rcw Kwok,K Xu,Y Xia,Y Li (2011). Text mining and probabilistic language modeling for online review spam detecting.
Raymond Lau,S Liao,Ron Chi-Wai Kwok,Kaiquan Xu,Yunqing Xia,Yuefeng Li (2011). Text mining and probabilistic language modeling for online review spam detection.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

MD Towhidul Islam Robin. 2019. "Cloud based Framework for Fake Review Detection". Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 19 (GJCST Volume 19 Issue D4).

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GJCST Volume 19 Issue D4

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Classification

GJCST-D Classification F.1.m

Submission ReceivedDecember 9, 2018
Peer Review Double Blind
Handling Editor
Accepted December 31, 2018
Published January 15, 2019

Version of record

v1.2

Issue date

November 14, 2019

Language

English

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Article Matrices

Total Score: 141

Country: Bangladesh

Subject: Global Journal of Computer Science and Technology

Authors: MD Towhidul Islam Robin (PhD/Dr. count: 0)

View Count (all-time): 478

Total Views (Real + Logic): 1587

Total Downloads (simulated): 126

Publish Date: 2019 01, Tue

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Total Views: 1.6K

Total Downloads: 126

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