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  • 1 SPRU—Science and Technology Policy Research, The Freeman Centre, University of Sussex, Brighton, BN1 9QE UK
  • | 2 Science and Technology Policy Research and Information Center, National Applied Research Laboratories, 14 F., No. 106, Sec. 2, He-Ping E. Rd., Taipei, 106 Taiwan
  • | 3 Graduate Institute of Technology and Innovation Management, National Chengchi University, No. 64, Sec. 2, Chih-Nan Rd., Wenshan, Taipei, 116 Taiwan
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Abstract  

This study proposes an empirical way for determining probability of network tie formation between network actors. In social network analysis, it is a usual problem that information for determining whether or not a network tie should be formed is missing for some network actors, and thus network can only be partially constructed due to unavailability of information. This methodology proposed in this study is based on network actors’ similarities calculations by Vector-Space Model to calculate how possible network ties can be formed. Also, a threshold value of similarity for deciding whether or not a network tie should be generated is suggested in this study. Four ontology-based knowledge networks, with journal paper or research project as network actors, constructed previously are selected as the targets of this empirical study: (1) Technology Foresight Paper Network: 181 papers and 547 keywords, (2) Regional Innovation System Paper Network: 431 papers and 1165 keywords, (3) Global Sci-Tech Policy Paper Network: 548 papers and 1705 keywords, (4) Taiwan’s Sci-Tech Policy Project Network: 143 research projects and 213 keywords. The four empirical investigations allow a cut-off threshold value calculated by Vector-Space Model to be suggested for deciding the formation of network ties when network linkage information is unavailable.

Manuscript submission: http://www.editorialmanager.com/scim/

  • Impact Factor (2019): 2.867
  • Scimago Journal Rank (2019): 1.210
  • SJR Hirsch-Index (2019): 106
  • SJR Quartile Score (2019): Q1 Computer Science Apllications
  • SJR Quartile Score (2019): Q1 Library and Information Sciences
  • SJR Quartile Score (2019): Q1 Social Sciences (miscellaneous)
  • Impact Factor (2018): 2.770
  • Scimago Journal Rank (2018): 1.113
  • SJR Hirsch-Index (2018): 95
  • SJR Quartile Score (2018): Q1 Library and Information Sciences
  • SJR Quartile Score (2018): Q1 Social Sciences (miscellaneous)

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Scientometrics
Language English
Size B5
Year of
Foundation
1978
Volumes
per Year
4
Issues
per Year
12
Founder Akadémiai Kiadó
Founder's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Publisher Akadémiai Kiadó
Springer Nature Switzerland AG
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
CH-6330 Cham, Switzerland Gewerbestrasse 11.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 0138-9130 (Print)
ISSN 1588-2861 (Online)