Paper Info
Title
Analyzing future communities in growing citation networks.
Abstract
Citation networks contain temporal information about what researchers are interested in at a certain time. A community in such a network is built around either a renowned researcher or a common research field; either way, analyzing how the community will change in the future will give insight into the research trend in the future. The paper proposes methods to analyze how communities change over time in the citation network graph without additional external information and based on node and link prediction and community detection. Different combinations of the proposed methods are also analyzed. Experiments show that the proposed methods can identify the changes in citation communities multiple years in the future with performance differing according to the analyzed time span. Furthermore, the method is shown to produce higher performance when analyzing communities to be disbanded and to be formed in the future.
Year
DOI
Venue
2014
10.1145/2513549.2513553
UnstructureNLP@CIKM
Keywords
Field
DocType
Community,Topic detection,Link prediction,Citation network,Community detection
Data science,Data mining,Graph,Information retrieval,Computer science,Citation,Citation network
Journal
Volume
ISSN
Citations 
69
0950-7051
2
PageRank 
References 
Authors
0.40
21
2
Name
Order
Citations
PageRank
Sukhwan Jung162.55
Aviv Segev224921.04