Paper Info
Title
Statistical study of characteristics of online reading behavior networks in university digital library
Abstract
Composed of a large number of interacting nodes, an online reading behavior network (ORBN) in a university digital library constitutes a large-scale online social network, which can be modeled as a complex system. Online social networks have been investigated intensively by many researchers over the past several years. However, there is little research on the online reading behaviors in university digital libraries. In this paper, we investigate the statistical characteristics of ORBNs in university digital libraries. This study reveals that the degree distribution of an online reading behavior network obeys the exponential distribution. In addition, the small-world phenomenon is observed in ORBNs. This study also compares the statistical characteristics of different types of ORBNs. The results show that the statistical characteristics of online reading behavior sub-networks remain consistent over multiple school years. However, over every four school years, differences are identified between the global ORBN and its sub-networks.
Year
DOI
Venue
2019
10.1007/s11280-018-0593-y
World Wide Web
Keywords
Field
DocType
Statistical characteristics, Online reading behavior network, University digital library, Complex networks
Data science,Social network,Computer science,Exponential distribution,Artificial intelligence,Degree distribution,Complex network,Digital library,Phenomenon,Machine learning
Journal
Volume
Issue
ISSN
22.0
SP3
1573-1413
Citations 
PageRank 
References 
0
0.34
12
Authors
6
Name
Order
Citations
PageRank
Lihong Han101.01
Gaofeng Zhang272.83
Binbin Yong3215.23
Qiang He420121.72
Fang Feng561.51
Qingguo Zhou610329.48