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A New Approach to Handling Erroneous Reviews in Opinion Mining

Kirti Kushwah1 , Rajendra Kumar Gupta2

Section:Review Paper, Product Type: Journal Paper
Volume-7 , Issue-7 , Page no. 54-62, Jul-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i7.5462

Online published on Jul 31, 2019

Copyright © Kirti Kushwah, Rajendra Kumar Gupta . 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: Kirti Kushwah, Rajendra Kumar Gupta, “A New Approach to Handling Erroneous Reviews in Opinion Mining,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.7, pp.54-62, 2019.

MLA Style Citation: Kirti Kushwah, Rajendra Kumar Gupta "A New Approach to Handling Erroneous Reviews in Opinion Mining." International Journal of Computer Sciences and Engineering 7.7 (2019): 54-62.

APA Style Citation: Kirti Kushwah, Rajendra Kumar Gupta, (2019). A New Approach to Handling Erroneous Reviews in Opinion Mining. International Journal of Computer Sciences and Engineering, 7(7), 54-62.

BibTex Style Citation:
@article{Kushwah_2019,
author = {Kirti Kushwah, Rajendra Kumar Gupta},
title = {A New Approach to Handling Erroneous Reviews in Opinion Mining},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2019},
volume = {7},
Issue = {7},
month = {7},
year = {2019},
issn = {2347-2693},
pages = {54-62},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4720},
doi = {https://doi.org/10.26438/ijcse/v7i7.5462}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i7.5462}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4720
TI - A New Approach to Handling Erroneous Reviews in Opinion Mining
T2 - International Journal of Computer Sciences and Engineering
AU - Kirti Kushwah, Rajendra Kumar Gupta
PY - 2019
DA - 2019/07/31
PB - IJCSE, Indore, INDIA
SP - 54-62
IS - 7
VL - 7
SN - 2347-2693
ER -

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Abstract

In the areas of marketing and electronic advertising, Opinion Mining has a broader domain. The advertiser must analyze the performance / popularity of the advertisements he has posted on the site. The mechanism based on the star rating can be fraudulent, due to robots or automatic responders. Therefore, it is necessary to analyze the current entity system or products using reviews (comments). Opinion Mining refers to the extraction of those lines or phrases in the huge raw data that express an opinion. On the other hand Sentimental Analysis is the analysis of feelings identifies the polarity (sentiment) of the opinion that is extracted from the review. Today, social networking sites and online shopping sites are used by users to express their opinion on products, events, peoples etc. Many users that express their opinion regarding any entity/Product, there may be chances that reviews are not written in correct form (Dictionary). Because of reviews available on these sites may contain noise such as spelling errors, typographical errors, standard abbreviations, and elegant writing. It is necessary to make data noise-free so that it can be used for opinion extraction. This paper describe a framework that was proposed to conduct opinion analysis of noisy reviews using techniques such as calculate similarity of terms and frequency of the document. The reviews of different products have been tested by this framework and the corresponding result is shown in negative (-ve) and positive (+ve ) form. The results are satisfactory for all the tested products.

Key-Words / Index Term

Opinion mining, Sentiment Analysis, Opinion extraction, Document Frequency

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