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» Finding Strongly Knit Clusters in Social Networks
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HICSS
2007
IEEE
110views Biometrics» more  HICSS 2007»
14 years 14 days ago
Social Network and Genre Emergence in Amateur Flash Multimedia
Research on digital media tends to characterize the emergence of new genres without reference to social networks, even though “community” and “social interaction” are invo...
John C. Paolillo, Jonathan Warren, Breanne Kunz
EDBT
2012
ACM
228views Database» more  EDBT 2012»
11 years 8 months ago
Finding maximal k-edge-connected subgraphs from a large graph
In this paper, we study how to find maximal k-edge-connected subgraphs from a large graph. k-edge-connected subgraphs can be used to capture closely related vertices, and findin...
Rui Zhou, Chengfei Liu, Jeffrey Xu Yu, Weifa Liang...
KDD
2009
ACM
173views Data Mining» more  KDD 2009»
14 years 6 months ago
Constant-factor approximation algorithms for identifying dynamic communities
We propose two approximation algorithms for identifying communities in dynamic social networks. Communities are intuitively characterized as "unusually densely knit" sub...
Chayant Tantipathananandh, Tanya Y. Berger-Wolf
AAAI
2006
13 years 7 months ago
Identification and Evaluation of Weak Community Structures in Networks
Identifying intrinsic structures in large networks is a fundamental problem in many fields, such as engineering, social science and biology. In this paper, we are concerned with c...
Jianhua Ruan, Weixiong Zhang
SOUPS
2010
ACM
13 years 10 months ago
Feasibility of structural network clustering for group-based privacy control in social networks
Users of social networking sites often want to manage the sharing of information and content with different groups of people based on their differing relationships. However, group...
Simon Jones, Eamonn O'Neill