Fake Smartwatch Review Monitoring and Analysis System

The quick spread of Web advances and the Web has achieved a colossal measure of client
produced content. Simultaneously, an expanding number of exercises have gone to an online
model, gaining by the Internet spread and progression. E-commerce is one of the fields that
have thrived in this condition, enabling buyers to take part in online exchanges in a phenomenal
usability. Purchasers can contribute their sentiments, through surveys, to give analysis on the
quality and estimation of obtained items and administrations. An expanding number of
imminent clients consider the overall population supposition before spending their store by
perusing on the web audits. The impact of positive or negative feelings is along these lines of
principal significance to organizations and specialist co-ops.
This prompted the presence of obscure works on, including the formation of tricky online audits
to advance or downgrade items by controlling buyer feeling. This supposition or review
spamming, is viewed as a noteworthy issue in the present online world and right now, explore
has been embraced to recognize deceitful substance in online review and thusly, secure
customer interests. Up until now, look into has been isolated among location of phony audits,
survey spammers and spammer groups, and various endeavours have yielded promising
outcomes by gaining by specific pieces of information and qualities of spamming movement
and creating devoted procedures and investigation strategies.
The main objective of this project is to develop system to detect and remove fake reviews done
on a smartwatch product. There are 2 main objectives that need to achieve, 1) To implement
the usage of API classifiers in determining the positive or negative sentiment. 2) To utilize the
usage of IP Address, Account Used as a method in detecting fake review Reviews are poised
as the benchmark for the quality of the product before purchasing it physically. This is mainly
because the consumer would want the business organizations to have integrity in selling the
said product. The fake reviewers have a purpose to either boost the viewing of the product or
to just spam unnecessary comments towards the products. Either way, it destroys the reliability
business organizations to sell the product and the platform of them promoting the product. The
application will be develop using a data mining methodology which consists of 6 key elements
which are Research and Survey, Data Acquisition, Data Integration, Fake Review
Identification Labelling, Pre-processing, Processing Stage and Evaluate the Approach.
Followed by Sentimental Analysis Process in Fake Review Identification Labelling.