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Community Mining: from Discovery to Evaluation and Visualization Open Access


Other title
social network analysis
local community framework
community visualization
relative validity criteria
community mining
Type of item
Degree grantor
University of Alberta
Author or creator
Fagnan, Justin J
Supervisor and department
Zaiane, Osmar (Computing Science)
Examining committee member and department
Zaiane, Osmar (Computing Science)
Barbosa, Denilson (Computing Science)
Arazy, Ofer (Business)
Department of Computing Science

Date accepted
Graduation date
Master of Science
Degree level
Social networks are ubiquitous. They can be extracted from our purchase history at on-line retailers, our cellphone bills, and even our health records. Mining tech- niques that can accurately and efficiently identify interesting patterns in these net- works are sought after by researchers from a variety of fields. The patterns they seek often take the shape of communities, which are tightly-knit groups of nodes that are more strongly related within the group than outside of the group. This thesis proposes a series of algorithms that both accurately identify and evaluate communities in social networks. In particular we show that relative valid- ity criteria from the field of database clustering do not serve as adequate substitutes in lieu of a ground truth. Furthermore we propose a novel community mining al- gorithm that considers the number of internal and external triads within each com- munity. Finally, we present two visualization algorithms that visually expose pre- viously difficult to obtain information regarding the structure and relationships of communities. We conclude this thesis with a brief summary of some open problems in the area of community mining and visualization.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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