DocumentCode :
531481
Title :
Empirical Analysis and Multiple Level Views in Massive Social Networks
Author :
Ye, Qi ; Wu, Bin ; Gao, Yuan ; Wang, Bai
Author_Institution :
Sch. of Comput. Sci., Beijing Univ. of Posts & Telecommun., Beijing, China
Volume :
1
fYear :
2010
fDate :
Aug. 31 2010-Sept. 3 2010
Firstpage :
541
Lastpage :
544
Abstract :
With the emergence of massive social media, massive social networks have led to a huge interest in data analysis. In this paper, we propose an empirical study on several massive social networks including 4 mobile call graphs, a fixed-line call graph, two co-authorship networks and two Email networks. We find that call graphs tend to be more locality than the co-authorship networks and Email networks. To our surprise, we even find that there is no significant relations between community sizes and their quality scores for most extracted communities. We also find that some very huge community with high mean quality values, and we can not find the universal "V" shape in their mean quality values.
Keywords :
data analysis; graph theory; information networks; social networking (online); coauthorship network; data analysis; email network; empirical analysis; fixed line call graph; massive social media; massive social network; mean quality value; mobile call graph; multiple level view; universal V shape; Call graphs; Community; Graph Mining; Social Network Analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference on
Conference_Location :
Toronto, ON
Print_ISBN :
978-1-4244-8482-9
Electronic_ISBN :
978-0-7695-4191-4
Type :
conf
DOI :
10.1109/WI-IAT.2010.48
Filename :
5616338
Link To Document :
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