Key Author Analysis in 1 and 1.5 Degree Egocentric Collaboration Network

被引:0
|
作者
Bihari, Anand [1 ]
Tripathi, Sudhakar [1 ]
机构
[1] Natl Inst Technol Patna, Dept Comp Sci & Engn, Patna, Bihar, India
来源
COMPUTATIONAL INTELLIGENCE IN DATA MINING, CIDM 2016 | 2017年 / 556卷
关键词
Social network; Degree centrality; Closeness centrality; Egocentric network; Density; CENTRALITY;
D O I
10.1007/978-981-10-3874-7_17
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The evaluation of scientific performance of an individual author in the research community is based on total number of articles published, citation count, average citation count, h-index, etc. But generally research work is done by the group of researchers and the performance of individual may depends on the neighbors' researchers. So the evaluation of scientific impact of an individual will carry based on their immediate neighbors. In this paper, we form a 1 degree and 1.5 degree egocentric network of every node and convey the degree centrality, closeness centrality, and density to estimate the scientific efficacy of an individual. Finally, compare the results of all those types of network and found that the 1.5 degree egocentric networks are useful to appraise the performance of researchers.
引用
收藏
页码:173 / 180
页数:8
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