Spammer Detection and Fake User Identification in E-Commerce Site
P.S. Gayke1 , Snehal Kardile2 , Nutan Dongare3 , Shweta Pathare4 , Pallavi Sakat5
Section:Research Paper, Product Type: Journal Paper
Volume-9 ,
Issue-7 , Page no. 22-25, Jul-2021
CrossRef-DOI: https://doi.org/10.26438/ijcse/v9i7.2225
Online published on Jul 31, 2021
Copyright © P.S. Gayke, Snehal Kardile, Nutan Dongare, Shweta Pathare, Pallavi Sakat . 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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How to Cite this Paper
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IEEE Style Citation: P.S. Gayke, Snehal Kardile, Nutan Dongare, Shweta Pathare, Pallavi Sakat, “Spammer Detection and Fake User Identification in E-Commerce Site,” International Journal of Computer Sciences and Engineering, Vol.9, Issue.7, pp.22-25, 2021.
MLA Style Citation: P.S. Gayke, Snehal Kardile, Nutan Dongare, Shweta Pathare, Pallavi Sakat "Spammer Detection and Fake User Identification in E-Commerce Site." International Journal of Computer Sciences and Engineering 9.7 (2021): 22-25.
APA Style Citation: P.S. Gayke, Snehal Kardile, Nutan Dongare, Shweta Pathare, Pallavi Sakat, (2021). Spammer Detection and Fake User Identification in E-Commerce Site. International Journal of Computer Sciences and Engineering, 9(7), 22-25.
BibTex Style Citation:
@article{Gayke_2021,
author = {P.S. Gayke, Snehal Kardile, Nutan Dongare, Shweta Pathare, Pallavi Sakat},
title = {Spammer Detection and Fake User Identification in E-Commerce Site},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2021},
volume = {9},
Issue = {7},
month = {7},
year = {2021},
issn = {2347-2693},
pages = {22-25},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5359},
doi = {https://doi.org/10.26438/ijcse/v9i7.2225}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v9i7.2225}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5359
TI - Spammer Detection and Fake User Identification in E-Commerce Site
T2 - International Journal of Computer Sciences and Engineering
AU - P.S. Gayke, Snehal Kardile, Nutan Dongare, Shweta Pathare, Pallavi Sakat
PY - 2021
DA - 2021/07/31
PB - IJCSE, Indore, INDIA
SP - 22-25
IS - 7
VL - 9
SN - 2347-2693
ER -
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Abstract
Sentiment analysis is a technique which is used for Natural language Processing, text analysis, text pre-processing etc. are the trending research field in current time. Sentiment analysis using different techniques and tools for analyze and arrange the unstructured data in a manner that objective results can be generated from them. By using these techniques, allow a computer to understand what is being said by humans. Sentiment analysis uses different techniques to determine the sentiment from a text or sentence or expression. The Internet is a huge source of natural language. People share their thoughts and experiences which are subjective in nature. Many a time, it is difficult for customer to identify whether the product shown by seller is good or bad. Companies may also unaware of customer requirements. Based on product reviews it is necessary to understand the perspective of customer towards a particular product. However, these are in huge amount; therefore a summary of positive and negative reviews needs to be generated. In this project, the main focus is on the review of products and techniques used for extract feature wise summary of the product and analyzed them to form an authentic review. Future work will include more product reviews websites and will focus on higher level natural language processing tasks. Using best and new techniques or tool for more accurate result in which the system except only those keywords which are in dataset rest of the words are eliminated by the system.
Key-Words / Index Term
Sentiment Analysis, Polarity, Natural Language Processing, Product reviews
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