Page 239 - JOURNAL OF LIBRARY SCIENCE IN CHINA 2015 Vol. 41

238 Journal of Library Science in China, Vol. 7, 2015

are an important information source of academic blog communication; formal publications can
offer discussion topics for academic blog communication; formal publications sometimes cite
the academic posts; the real academic status of a blogger has a significant influence on his/her
academic blog communication, etc.
This paper has certain limitations since we only take one of the Chinese academic blog
communities as our data source. Other academic blog communities, especially English-language
communities, will be studied and compared to this community in future research. Additionally, time is
an important factor impacting academic blog communication; it is important to consider a diachronic
study of the academic blog community to obtain more comprehensive findings and results.

A review on link prediction of scientific knowledge network
1 ∗
Bin ZHANG & Feicheng MA

Currently, the research about link prediction of knowledge network is scattered in the fields of
Statistical Physics, Computer Science, Complex Networks and Library and Information Science.
From the perspective of Library and Information Science, this paper mainly reviews researches on
link prediction of knowledge network and systematically analyzes previous researches.
This paper used“link prediction”as topic to retrieve the literatures in WoS, and got 300
records. Using CitNetExplorer to analyze the direct citation relationships among the 300 records,
we obtain the highly cited interrelated literatures to review on current link prediction types and
research ideas.
Link prediction can be classified into two types: the static and the dynamic, and the
corresponding dataset partition methods are different. The former uses random sampling, while
the latter needs to consider the temporal state. In the field of Library and Information Science,
knowledge networks vary in size and scale. So the link prediction of such knowledge networks
uses the similarity-based algorithms in order to reduce computing complexity, but also introduce
certain semantic and attribute information to ensure the accuracy of prediction.
This paper divides the knowledge network into homogeneous and heterogeneous networks.
For the link prediction of homogeneous network, this paper reviews on the research progress
from the aspects of co-authorship network, citation network and bipartite network. The co-
authorship network can be viewed as an undirected network, and is the easiest way to describe
the real network system. This paper summarizes the predictors and steps in link prediction of co-
authorship network and examines its prediction effect from author, institution, and country level.
The citation networks can be viewed as a directed network, and is the first proposed knowledge
network. Compared with the co-authorship network, the citation network not only has the structure

* Correspondence should be addressed to Bin ZHANG, Email: zb0205@126.com, ORCID: 0000-0002-5591-7874