Increasing importance of ’networking’ in practical management guides and also by the proliferation of ’social networking’
Social networks produce an enormous quantity of data. Facebook consists of over 400 million active users sharing over 5 billion pieces
of information each month. People are interconnected through online social networks such as Twitter, Facebook, LinkedIn Instagram
etc. Social network analysis has gained prominence due to its use in different applications and analyzing how the members of network
interact, share information or establish relationships, useful knowledge about them and their relations can be extracted. In this paper
we present an approach to analyze the Twitter and Facebook profiles based on the location. The locations of these users should selected
by the user. The proposed analysis is comparing the Facebook and Twitter profiles based on the location and extracting the tweets or
comments posted on the network based on the users interested area. Thus the work is related to the big data in the area of big data
analytics.
Published In:IJCSN Journal Volume 7, Issue 2
Date of Publication : April 2018
Pages : 61-66
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Hindu Sindhura : Computer Science and Engineering, Visvesvaraya Technology University,
BMS Institute Of Technology And Management
Bangalore, Karnataka, India.
Anand.R : Asst. Professor Computer Science and Engineering,
BMS Institute Of Technology And Management
Bangalore, Karnataka , India.
Dr.Rajashekar M Patil : Professor Information Science Engineering,
HKBK College Of Engineering
Bangalore, Karnataka, India.
Big data Analytics, Twitter and Facebook mining, social networking Analysis
We present an approach to analyze the Twitter and
Facebook profiles based on the location. The locations of
these users should selected by the user.
