DocumentCode :
3102252
Title :
Large-Scale Social Network Analysis Based on MapReduce
Author :
Liu, Guojun ; Zhang, Ming ; Yan, Fei
Author_Institution :
Sch. of EECS, Peking Univ., Beijing, China
fYear :
2010
fDate :
26-28 Sept. 2010
Firstpage :
487
Lastpage :
490
Abstract :
Social Networks Service (SNS), is becoming more and more popular and a lot of studies have been carried out in this active field. However, traditional analysis methods based on single machines is not suitable because the network is growing too large. MapReduce, a programming paradigm proposed by Google, gives us a new approach to solve large-scale social networks analysis problem by making use of the power of multi-machines. In this paper, we use Hadoop - an open source implementation of MapReduce - to conduct a series of analyses on large-scale social networks including several distributions, clustering coefficient and diameter. We believe that our work will shed light on the study of measuring large-scale social networks.
Keywords :
Internet; social networking (online); Google; Hadoop; large-scale social network analysis; mapreduce; social networks service; Algorithm design and analysis; Clustering algorithms; Data models; Educational institutions; Internet topology; Programming; Social network services; MapReduce; Social Network; analysis; large-scale;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Aspects of Social Networks (CASoN), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-8785-1
Type :
conf
DOI :
10.1109/CASoN.2010.115
Filename :
5636636
Link To Document :
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