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Detection of Fake Reviews through Opinion Mining: A Survey

Ashwini M C1 , M C Padma2

Section:Survey Paper, Product Type: Journal Paper
Volume-8 , Issue-3 , Page no. 119-125, Mar-2020

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v8i3.119125

Online published on Mar 30, 2020

Copyright © Ashwini M C, M C Padma . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Ashwini M C, M C Padma, “Detection of Fake Reviews through Opinion Mining: A Survey,” International Journal of Computer Sciences and Engineering, Vol.8, Issue.3, pp.119-125, 2020.

MLA Style Citation: Ashwini M C, M C Padma "Detection of Fake Reviews through Opinion Mining: A Survey." International Journal of Computer Sciences and Engineering 8.3 (2020): 119-125.

APA Style Citation: Ashwini M C, M C Padma, (2020). Detection of Fake Reviews through Opinion Mining: A Survey. International Journal of Computer Sciences and Engineering, 8(3), 119-125.

BibTex Style Citation:
@article{C_2020,
author = {Ashwini M C, M C Padma},
title = {Detection of Fake Reviews through Opinion Mining: A Survey},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2020},
volume = {8},
Issue = {3},
month = {3},
year = {2020},
issn = {2347-2693},
pages = {119-125},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5063},
doi = {https://doi.org/10.26438/ijcse/v8i3.119125}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v8i3.119125}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5063
TI - Detection of Fake Reviews through Opinion Mining: A Survey
T2 - International Journal of Computer Sciences and Engineering
AU - Ashwini M C, M C Padma
PY - 2020
DA - 2020/03/30
PB - IJCSE, Indore, INDIA
SP - 119-125
IS - 3
VL - 8
SN - 2347-2693
ER -

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Abstract

Opinion mining has played a momentous role in providing product recommendations to users. An efficient recommendation system helps in improving customer satisfaction and also enhances business. The credibility of purchasing a product highly depends on online reviews. Since not all online reviews are truthful and trustworthy, it is important to develop techniques for detecting review spam, it is possible to conduct review spam detection using various machine learning techniques. We survey the prominent machine learning techniques that have been proposed to solve the problem of review spam detection. This literature survey is done to study the various fake review detection techniques in detail.    

Key-Words / Index Term

Sentiment Analysis; opinion Mining; Fake reviews; Machine learning; Recommendation Systems

References

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