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Structural Role Mining in Social Networks

  • Author / Creator
    Abnar, Afra
  • All along their lives, individuals take roles in their interactions with each other. This behaviour is known as the role-taking characteristic of human beings. We refer to these roles as social roles that are the primary components of societies. Identifying social roles in a society helps to better analyze the social phenomena. Consequently, it can be beneficial in the search for influentials, trustworthy peo- ple, idea innovators, etc. With this intention, we propose the structural social role mining (SSRM) framework to identify roles, study their changes, and analyze their impacts on the underlying social network. More specifically, we define four fun- damental roles called leader, outermost, mediator, and outsider. Subsequently, we suggest methodologies to identify these roles within a social network. While ex- ploring our proposed methodologies for identifying the aforementioned roles, we develop two new variants of Betweenness centrality (BC): LBetweenness (LBC) and CBetweenness (CBC). Motivated by time complexity, these two centrality mea- sures are computed more efficiently compared to Betweenness centrality especially in large social networks. Eventually, we identify and study changes of roles in the Enron communication network using our proposed framework. According to our results, individuals serving as leaders or mediators were important people in the Enron organization. Moreover, identifying roles as well as their changes through consecutive timeframes could be informative and thus could be used as a clue for further investigations.

  • Subjects / Keywords
  • Graduation date
    2014-06
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R35H7C272
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
    • Department of Computing Science
  • Supervisor / co-supervisor and their department(s)
    • Zaiane, Osmar (Computing Science)
  • Examining committee members and their departments
    • Barbosa, Denilson (Computing Science)
    • Rathi, Dinesh (Library Science)