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  • 1 Department of Informatics, TU München, Boltzmannstr. 3, 85478 Garching, Germany fuchsc@in.tum.de
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Abstract

This paper analyzes whether methods from social network analysis can be adopted for the modeling of scientific fields in order to obtain a better understanding of the respective scientific area. The approach proposed is based on articles published within the respective scientific field and certain types of nodes deduced from these papers, such as authors, journals, conferences and organizations. As a proof of concept, the techniques discussed here are applied to the field of ‘Mobile Social Networking’. For this purpose, a tool was developed to create a large data collection representing the aforementioned field. The paper analyzes various views on the complete network and discusses these on the basis of the data collected on Mobile Social Networking. The authors demonstrate that the analysis of particular subgraphs derived from the data collection allows the identification of important authors as well as separate sub-disciplines such as classic network analysis and sensor networks and also contributes to the classification of the field of ‘Mobile Social Networking’ within the greater context of computer science, applied mathematics and social sciences. Based on these results, the authors propose a set of concrete services which could be offered by such a network and which could help the user to deal with the scientific information process. The paper concludes with an outlook upon further possible research topics.

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  • 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)