  Online reviews have become a valuable and significant resource, for not only
consumers but companies, in decision making. In the absence of a trusted
system, highly popular and trustworthy internet users will be assumed as
members of the trusted circle. In this paper, we describe our focus on
quarantining deceiving Yelp's users that employ both review spike detection
(RSD) algorithm and spam detection technique in bridging review networks (BRN),
on extracted key features. We found that more than 80% of Yelp's accounts are
unreliable, and more than 80% of highly-rated businesses are subject to
spamming.
