Profile Matching Of Anonymous Users in Multiple Social Media Networks

Abstract

The SMN proves to be the best platform for information retrieval. However, identifying unknown and identical users on multiple social media application is still an unsolved problem. People use different  social  media  for different  purpose; the  idea  of  integrating  multiple  social  media  application  can  take  the  research  a  step  forward. The  main  idea  of  this  project  is  to  identify  alias  and  identical  accounts  by  merging  multiple  SMN  in  order  to  get  complete  information  about  a particular  user.  In social media networks, profile details of one user  can  be  used  by  others  to  create  account  with  original user   identity   or   the   original   user   may   have   multiple accounts   in   multiple   social   media   sites.   Discovery   of multiple  accounts  that  belong  to  the  same  person  is  an interesting  and  challenging work  in  social  media analysis. Profiles, contents  and  network  structures  can  be  used  for user identification in social media sites. In this project, we develop a methodology Friend Relationship - Based User Identification (FRUI) algorithm for mapping individuals on cross application SMN’s. The friend cycle of every individual differs therefore, accuracy of our result will be maintained if we use friend list as a key component to analyse cross application social media networks. We also focus on using two more methods to improve efficiency of our algorithm. Our study has shown that FRUI is effective to analyze and de -anonymize social media.