Cloud based Framework for Fake Review Detection

α
MD Towhidul Islam Robin
MD Towhidul Islam Robin
α Stamford University Bangladesh

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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
  1. Snehal Dixit,A Agrawal (2013). SURVEY ON REVIEW SPAM DETECTION.
  2. M Ott,Y Choi,C Cardie,J Hancock (2011). Finding deceptive opinion spam by any stretch of the imagination.
  3. N Jindal,B Liu (2007). Opinion spam and analysis.
  4. Asa Hammad (2003). An extensive empirical study of feature selection metrics for text classification.
  5. R Lau,S Liao,Rcw Kwok,K Xu,Y Xia,Y Li (2011). Text mining and probabilistic language modeling for online review spam detecting.
  6. 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.

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. \u201cCloud based Framework for Fake Review Detection\u201d. Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 19 (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
Classification
GJCST-D Classification: F.1.m
Version of record

v1.2

Issue date

November 14, 2019

Language
en
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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.

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Cloud based Framework for Fake Review Detection

MD Towhidul Islam Robin
MD Towhidul Islam Robin Stamford University Bangladesh

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