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Detecting Fraud Reviews of Apps Using Sentiment Analysis

S. Sabeena1

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-1 , Page no. 365-368, Jan-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i1.365368

Online published on Jan 31, 2019

Copyright © S. Sabeena . 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: S. Sabeena, “Detecting Fraud Reviews of Apps Using Sentiment Analysis,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.365-368, 2019.

MLA Style Citation: S. Sabeena "Detecting Fraud Reviews of Apps Using Sentiment Analysis." International Journal of Computer Sciences and Engineering 7.1 (2019): 365-368.

APA Style Citation: S. Sabeena, (2019). Detecting Fraud Reviews of Apps Using Sentiment Analysis. International Journal of Computer Sciences and Engineering, 7(1), 365-368.

BibTex Style Citation:
@article{Sabeena_2019,
author = {S. Sabeena},
title = {Detecting Fraud Reviews of Apps Using Sentiment Analysis},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2019},
volume = {7},
Issue = {1},
month = {1},
year = {2019},
issn = {2347-2693},
pages = {365-368},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3513},
doi = {https://doi.org/10.26438/ijcse/v7i1.365368}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i1.365368}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3513
TI - Detecting Fraud Reviews of Apps Using Sentiment Analysis
T2 - International Journal of Computer Sciences and Engineering
AU - S. Sabeena
PY - 2019
DA - 2019/01/31
PB - IJCSE, Indore, INDIA
SP - 365-368
IS - 1
VL - 7
SN - 2347-2693
ER -

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Abstract

Sentiment analysis is one of the main tasks of Natural Language Processing (NLP). This analysis had gained more attention in recent years. In this paper, we tackled the problem of sentiment polarity categorization as one of the fundamental problems of sentiment analysis. A general process is proposed with detailed descriptions. Data used are online product reviews collected from Amazon.com. Experiment for sentence-level categorization and review-level categorization are performed with best outcomes. Finally, we give insight into our future work on sentiment analysis.

Key-Words / Index Term

Natural Language Processing(NLP), Sentiment Analysis, Sentence Level Categorization, Review Level Categorization

References

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