Paper Info
Title
A non-linear index to evaluate a journal's scientific impact
Abstract
The purpose of this study is to define a bibliometric indicator of the scientific impact of a journal, which combines objectivity with the ability to bridge many different bibliometric factors and in particular the side factors presented along with celebrated ISI impact factor. The particular goal is to determine a standard threshold value in which an independent self-organizing system will decide the correlation between this value and the impact factor of a journal. We name this factor ''Cited Distance Factor (CDF)'' and it is extracted via a well-fitted, recurrent Elman neural network. For a case study of this implementation we used a dataset of all journals of cell biology, ranking them according to the impact factor from the Web of Science Database and then comparing the rank according to the cited distance. For clarity reasons we also compare the cited distance factor with already known measures and especially with the recently introduced eigenfactor of the institute of scientific information (ISI).
Year
DOI
Venue
2010
10.1016/j.ins.2010.01.018
Inf. Sci.
Keywords
Field
DocType
bibliometric indicator,celebrated isi impact factor,non-linear index,distance factor,different bibliometric factor,impact factor,particular goal,scientific impact,case study,scientific information,side factor,cell biology,indexation,bibliometrics
Data science,CLARITY,Information retrieval,Ranking,Computer science,Eigenfactor,Objectivity (philosophy),Artificial intelligence,Bibliometrics,Artificial neural network,Machine learning,Impact factor
Journal
Volume
Issue
ISSN
180
11
0020-0255
Citations 
PageRank 
References 
8
0.57
24
Authors
4
Name
Order
Citations
PageRank
Sozon Papavlasopoulos1214.79
Marios Poulos210915.71
Nikolaos Korfiatis321715.15
George Bokos4887.97