UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
Call for Paper
Volume 11 | Issue 3 | March 2024

JETIREXPLORE- Search Thousands of research papers



WhatsApp Contact
Click Here

Published in:

Volume 8 Issue 6
June-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

Unique Identifier

Published Paper ID:
JETIR2106415


Registration ID:
310772

Page Number

d110-d112

Share This Article


Jetir RMS

Title

Fake Product Review Detection System Using Machine Learning

Abstract

Online systems people most of the time trust in products based on product reviews and ratings. Reviews have a great impact on a company or a brand profile. The company must examine market reactions to its products. Popular reviews, on the other hand, are difficult to track and arrange. In social media, many people viewpoints are difficult to manually process. The next step is to develop a mechanism for automatically categorizing favorable and negative public feedback. Customers will be able to see how the product performs in terms of consistency, efficiency, and guidance, which will provide prospective buyers a better knowledge of the product. The applicability of web contents from suppliers in order to fulfill client requirements by evaluating beneficial input is one such unfulfilled possibility. Good and bad reviews are important in determining customer demands and gathering product feedback from customers. Sentiment Analysis is a type of text analysis that collects contextual information from text. A large number of internet mobile phone ratings are studied in this study. We divided the text into positive and negative categories, as well as feelings of disappointment, expectation, disgust, trepidation, delight, regret, surprise, and confidence. This clearly defined category of feedback aids in a comprehensive evaluation of the product, allowing consumers to make better decisions.

Key Words

Machine Learning, Social Media, Text Mining, Sentiment Analysis, Semantic Analysis, Online Reviews

Cite This Article

"Fake Product Review Detection System Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.d110-d112, June-2021, Available :http://www.jetir.org/papers/JETIR2106415.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Fake Product Review Detection System Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppd110-d112, June-2021, Available at : http://www.jetir.org/papers/JETIR2106415.pdf

Publication Details

Published Paper ID: JETIR2106415
Registration ID: 310772
Published In: Volume 8 | Issue 6 | Year June-2021
DOI (Digital Object Identifier):
Page No: d110-d112
Country: osmanabad, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


Preview This Article


Downlaod

Click here for Article Preview

Download PDF

Downloads

0001041

Print This Page

Current Call For Paper

Jetir RMS