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KDD
2008
ACM
147views Data Mining» more  KDD 2008»
14 years 8 months ago
Mobile call graphs: beyond power-law and lognormal distributions
We analyze a massive social network, gathered from the records of a large mobile phone operator, with more than a million users and tens of millions of calls. We examine the distr...
Mukund Seshadri, Sridhar Machiraju, Ashwin Sridhar...
KDD
2008
ACM
284views Data Mining» more  KDD 2008»
14 years 8 months ago
Community evolution in dynamic multi-mode networks
A multi-mode network typically consists of multiple heterogeneous social actors among which various types of interactions could occur. Identifying communities in a multi-mode netw...
Lei Tang, Huan Liu, Jianping Zhang, Zohreh Nazeri
KDD
2009
ACM
173views Data Mining» more  KDD 2009»
14 years 8 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
APVIS
2006
13 years 9 months ago
How people read sociograms: a questionnaire study
Visualizing social network data into sociograms plays an important role in communicating information about network characteristics. Previous studies have shown that human percepti...
Weidong Huang, Seok-Hee Hong, Peter Eades
INTR
2007
120views more  INTR 2007»
13 years 7 months ago
Analysing Google rankings through search engine optimization data
Purpose – The purpose of this paper is to identify the most popular techniques used to rank a web page highly in Google. Design/methodology/approach – The paper presents the r...
Michael P. Evans