The Generation of Large Networks from Web-of-Science Data; preprint version

[Loet Leydesdorff]

The Generation of Large Networks from Web-of-Science Data
<http://arxiv.org/abs/1409.4898> 


Loet Leydesdorff, Gohar Feroz Khan, and Lutz Bornmann

 


During the 1990s, one of us developed a series of freeware routines
(http://www.leydesdorff.net/indicators) that enable the user to organize
downloads from the Web-of-Science (Thomson Reuters) into a relational
database, and then to export matrices for further analysis in various
formats (for example, for co-author analysis). The basic format of the
matrices displays each document as a case in a row that can be attributed
different variables in the columns. One limitation to this approach was
hitherto that relational databases typically have an upper limit for the
number of variables, such as 256 or 1024. In this brief communication, we
report on a way to circumvent this limitation by using txt2Pajek.exe,
available as freeware from http://www.pfeffer.at/txt2pajek/.

 

(Submitted on 17 Sep 2014; available at http://arxiv.org/abs/1409.4898)

.        apologies for cross-postings.

 

  _____  

Loet Leydesdorff 

University of Amsterdam
Amsterdam School of Communications Research (ASCoR)

 <mailto:loet at leydesdorff.net> loet at leydesdorff.net ;
<http://www.leydesdorff.net/> http://www.leydesdorff.net/ 
Honorary Professor,  <http://www.sussex.ac.uk/spru/> SPRU, University of
Sussex; 

Guest Professor  <http://www.zju.edu.cn/english/> Zhejiang Univ., Hangzhou;
Visiting Professor,  <http://www.istic.ac.cn/Eng/brief_en.html> ISTIC,
Beijing;

Visiting Professor,  <http://www.bbk.ac.uk/> Birkbeck, University of London;


 <http://scholar.google.com/citations?user=ych9gNYAAAAJ&hl=en>
http://scholar.google.com/citations?user=ych9gNYAAAAJ&hl=en  



 

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