Big data Analysis on Multiple Social Network

Abstract

This work analyzed the big data from four social network platforms with the aimed of discovering multiple view of users in social networks. The datasets were collected from Facebook, Twitter, Instagram, and Foursquare. Facebook was primarily used as ground truth. The dataset involved users from London and Singapore region only. Different human pattern behavior was observed and compared based on their gender and age groups. Learning human mobility and creating profile base on their visited locations was another contribution. The user mobility profile created was based on location preferences. The analysis results showed that females and males were leading in check-ins at Malls in Singapore compare to London region.