Excavating social circles via user interests

Diana Palsetia*, Md Mostofa Ali Patwary, Ankit Agrawal, Alok Choudhary

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The rapid evolution of modern social networks motivates the design of networks based on users’ interests. Using popular social media such as Facebook and Twitter, we show that this new perspective can bring more meaningful information about the networks. In this paper, we model user-interest-based networks by deducing intent from social media activities such as comments and tweets of millions of users in Facebook and Twitter, respectively. These interactive contents derive networks that are dynamic in nature as the user interests can evolve due to temporal and spatial activities occurring around the user. To excavate social circles, we develop an approach that iteratively removes the influence of the communities identified in the previous steps by widely used Clauset, Newman, and Moore (CNM) community detection algorithm. Experimental results show that our approach can detect communities at a much finer scale compared to the CNM algorithm. Our user-interest-based model and community extraction methodology together can be used to identify target communities in the context of business requirements.

Original languageEnglish (US)
Article number170
Pages (from-to)1-12
Number of pages12
JournalSocial Network Analysis and Mining
Volume4
Issue number1
DOIs
StatePublished - Jan 1 2014

Keywords

  • Analysis clustering
  • Community detection
  • Extraction
  • Graph partitioning
  • social network

ASJC Scopus subject areas

  • Information Systems
  • Communication
  • Media Technology
  • Human-Computer Interaction
  • Computer Science Applications

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