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.
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