Conference Paper2015Cited by 1

Fusion based approach to discovering social circles in EGO networks

A Kamal, MM Lutfe Elahi, Bruce Poon, M Ashraful Amin

2015 International Conference on Machine Learning and Cybernetics (ICMLC)

IEEE, Vol. 2, pp. 511–517

DOI: 10.1109/icmlc.2015.7340609URL

Abstract

Communication among people via social network generates enormous amount of data every day. This data can be valuable if they are properly organized. Only with the proper organization of these data into scalable structures, we will be able to find pattern in these data. A very important step in organizing these data is to organize the social network itself. The main challenge for users of social media is to organize their networks and content generated by them by categorizing their friends and the people they follow into different social circles. Social circles are actually lists of people from a person's friends that can be used for content filtering, privacy and sharing information only among those people in his/her circle. In this paper, we propose a method to automatically discovery of a person's potential overlapping social circles by usage of different community detection algorithms and clustering methods. Our approach performed significantly well as compared to classical community detection methods.

Keywords

  • social circles
  • community detection
  • personal networks
  • Social media
  • content filtering
  • clustering
  • overlapping communities
  • privacy

CCDS Authors

Prof. M Ashraful Amin, PhD
M Ashraful Amin, PhD

Prof. M Ashraful Amin, PhD

  • Founder Director, CCDS
  • Director, AI/ML, HCI & DS Wings

Professor

+1 more affiliation

Department of Information Sciences and Technology

George Mason University, USA

Published at

ACL, CHI, UbiComp, ECAI, WACV, PAKDD, IJCNN, ICPR, ICIP, HCII, CLEF, BLP, Scientific Reports, JMIR, IEEE Access, Smart Agricultural Technology, Frontiers in Computational Neuroscience, Diabetes Research and Clinical Practice, PLOS ONE

Research Interests

Machine Learning, Cognitive & Vision Science, Cybernetics, Surveillance & Security, ICT in Education, Health, & Agriculture, Human-Computer Interaction, Internet of Things, Robotics

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Cited By

  1. 1.Fei Ding, Yi Zhuang. (2018). Ego-network probabilistic graphical model for discovering on-line communities. Applied Intelligence, 48(9), 3038–3052[10.1007/s10489-018-1137-y]
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