DocumentCode :
120039
Title :
Research on Statistical Feature of Online Social Networks Based on Complex Network Theory
Author :
Xin Jin ; Jianyu Li
Author_Institution :
Sch. of Comput. Sci., Commun. Univ. of China, Beijing, China
fYear :
2014
fDate :
4-6 July 2014
Firstpage :
35
Lastpage :
39
Abstract :
At present, the study of complex networks include the geometric nature of the network, the formation mechanism of the network, the statistical law of the network evolution, the model property on the network, the structure stability of the network, and other issues like network evolution and dynamic mechanics, etc. There into, in the field of natural science, the basic measuring of the network research includes degree and its distribution characteristic, relevancy of degree, clustering and its distribution characteristics, shortest path and its distribution characteristics, sparsity and its distribution characteristics, and size distribution of connected groups. In order to depict the complex network topology, scholars have proposed many methods to describe the statistical parameter and measurement for complex network features. The OSN will be briefly analyzed below by using these important concepts. At last, the research significance of the online social network, the value of theory, potential applications and research direction in future have been summed up.
Keywords :
complex networks; network theory (graphs); social networking (online); statistical analysis; complex network theory; degree characteristic; degree relevancy; distribution characteristic; network evolution; network formation mechanism; network geometric nature; network structure stability; online social networks; statistical feature; statistical law; Communities; Complex networks; Correlation; Educational institutions; Social network services; Topology; Complex network; degree; online social network (OSN); sparsity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Sciences and Optimization (CSO), 2014 Seventh International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-5371-4
Type :
conf
DOI :
10.1109/CSO.2014.16
Filename :
6923631
Link To Document :
بازگشت